-----------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\1313537\Dropbox\Ramon y Cajal UAB\2024-2025\Multiple UESDs paper\PSRM R&R\placebo rep
> lication material\Placebo Preplication (Section D.6).log
  log type:  text
 opened on:  10 Feb 2025, 17:11:34

. 
. 
. /*******************************************************************************
>                        HARMONIZATION OF THE VARIABLES
> *******************************************************************************/
. 
. 
. 
. *************************** OCTOBER 1998 ***************************************
. 
. import spss using "CIS Studies\2307.sav", clear
(96 vars, 2,490 obs)

. 
. 
. ** date
. gen str_date= substr(FINAL,18,6) 

. tab str_date

   str_date |      Freq.     Percent        Cum.
------------+-----------------------------------
       1098 |          1        0.04        0.04
     011198 |          4        0.16        0.20
     021098 |         13        0.52        0.72
     021198 |         23        0.92        1.65
     031198 |          9        0.36        2.01
     041198 |         24        0.96        2.97
     261098 |        277       11.12       14.10
     271098 |        511       20.52       34.62
     281098 |        608       24.42       59.04
     291098 |        521       20.92       79.96
     301098 |        325       13.05       93.01
     311098 |        174        6.99      100.00
------------+-----------------------------------
      Total |      2,490      100.00

. replace str_date="" if str_date=="  1098" // for this respondent, the day of the interview is not availab
> le
(1 real change made)

. 
. gen date= date(str_date, "DMY", 2000) 
(1 missing value generated)

. format date %tdDDmonCCYY 

. replace date =. if date<td(26oct1998) | date>td(31oct1998) 
(73 real changes made, 73 to missing)

. 
. 
. ** incumbent
. gen votinc=1 if P33==2
(1,841 missing values generated)

. replace votinc=0 if P33!=2 & P33!=.
(1,840 real changes made)

. label variable votinc "Vote for the incumbent"

. 
. 
. ** gender
. gen female=P38-1
(1 missing value generated)

. 
. 
. ** age
. gen age=P39
(2 missing values generated)

. 
. 
. ** education
. recode P40A (1=1) (2=2) (3=3) (4=4) (6=5) (5=6) (7=7) (8/11=8) (13=9) (12=10) (14 99=.), gen(edu)
(677 differences between P40A and edu)

. 
. 
. ** employment status
. recode P42 (1=1 "employed") (4 5 =2 "unemployed") (6=3 "student") (2 3 =4 "retired") (7=5 "housework") (8
>  9 =.), gen(emplo)  
(1,556 differences between P42 and emplo)

. 
. 
. ** size of municipality
. clonevar munsz=TAMUNI

. 
. 
. ** ccaa
. rename CCAA ccaa

. 
. 
. ** survey id
. gen studyid="1098"

. 
. 
. ** random treatment variable 
. preserve

. 
. bysort date: gen date_unique= _n ==1 

. replace date_unique=. if date==.
(74 real changes made, 74 to missing)

. keep if date_unique==1
(2,484 observations deleted)

. set seed 1

. sample 1, count 
(5 observations deleted)

. scalar random_attdate = date 

. 
. restore

. 
. display %tdDDmonCCYY random_attdate
29oct1998

. gen randdate= random_attdate // creating a variable with the random date

. format randdate %tdDDmonCCYY

. scalar drop random_attdate

. 
. gen randtreat = 1 if date>randdate & date!=. // creating a variable for the random treatment
(1,991 missing values generated)

. replace randtreat = 0 if date<randdate
(1,396 real changes made)

. replace randtreat = . if date==randdate
(0 real changes made)

. label variable randtreat "random treatment"

. label define treat 0 "pre" 1 "post"

. label values randtreat treat

. 
. 
. 
. save "harmonized dataset\1998_10", replace  
(file harmonized dataset\1998_10.dta not found)
file harmonized dataset\1998_10.dta saved

. 
. 
. 
. 
. *************************** JANUARY 1999 ***************************************
. 
. import spss using "CIS Studies\2316.sav", clear
(106 vars, 2,493 obs)

. 
. 
. ** date
. gen str_date= substr(FINAL,18,6) 

. 
. gen date= date(str_date, "DMY", 2000) 

. format date %tdDDmonCCYY 

. replace date =. if date<td(27jan1999) | date>td(31jan1999) 
(391 real changes made, 391 to missing)

. 
. ** incumbent
. gen votinc=1 if P33==2
(1,827 missing values generated)

. replace votinc=0 if P33!=2 & P33!=.
(1,827 real changes made)

. label variable votinc "Vote for the incumbent"

. 
. 
. ** gender
. gen female=P37-1

. 
. 
. ** age
. gen age=P38
(1 missing value generated)

. replace age=. if age==99
(2 real changes made, 2 to missing)

. 
. 
. ** education
. recode P39A (1=1) (2=2) (3=3) (4=4) (6=5) (5=6) (7=7) (8/11=8) (13=9) (12=10) (14 99=.), gen(edu)
(693 differences between P39A and edu)

. 
. 
. ** employment status
. recode P41 (1=1 "employed") (4 5 =2 "unemployed") (6=3 "student") (2 3 =4 "retired") (7=5 "housework") (8
>  9 =.), gen(emplo)  
(1,466 differences between P41 and emplo)

. 
. 
. ** size of municipality
. clonevar munsz=TAMUNI

. 
. 
. ** ccaa
. rename CCAA ccaa

. 
. 
. ** survey id
. gen studyid="0199"

. 
. 
. ** random treatment variable 
. preserve

. 
. bysort date: gen date_unique= _n ==1 

. replace date_unique=. if date==.
(391 real changes made, 391 to missing)

. keep if date_unique==1
(2,488 observations deleted)

. set seed 12

. sample 1, count 
(4 observations deleted)

. scalar random_attdate = date 

. 
. restore

. 
. display %tdDDmonCCYY random_attdate
29jan1999

. gen randdate= random_attdate // creating a variable with the random date

. format randdate %tdDDmonCCYY

. scalar drop random_attdate

. 
. gen randtreat = 1 if date>randdate & date!=. // creating a variable for the random treatment
(1,382 missing values generated)

. replace randtreat = 0 if date<randdate
(246 real changes made)

. replace randtreat = . if date==randdate
(0 real changes made)

. label variable randtreat "random treatment"

. label define treat 0 "pre" 1 "post"

. label values randtreat treat

. 
. 
. save "harmonized dataset\1999_01", replace  
(file harmonized dataset\1999_01.dta not found)
file harmonized dataset\1999_01.dta saved

. 
. 
. 
. 
. ***************************** APRIL 1999 ***************************************
. 
. import spss using "CIS Studies\2324.sav", clear
(123 vars, 2,499 obs)

. 
. 
. ** date
. gen str_date= substr(FINAL,18,6) 

. tab str_date

   str_date |      Freq.     Percent        Cum.
------------+-----------------------------------
       0499 |          1        0.04        0.04
     200499 |          1        0.04        0.08
     210499 |         17        0.68        0.76
     220399 |          1        0.04        0.80
     220499 |        217        8.68        9.48
     230499 |        448       17.93       27.41
     240499 |        386       15.45       42.86
     250399 |          4        0.16       43.02
     250499 |        126        5.04       48.06
     260399 |          3        0.12       48.18
     260499 |        771       30.85       79.03
     270499 |        390       15.61       94.64
     280499 |         52        2.08       96.72
     290499 |         57        2.28       99.00
     300499 |         25        1.00      100.00
------------+-----------------------------------
      Total |      2,499      100.00

. replace str_date="" if str_date=="  0499" // for this respondent, the day of the interview is not availab
> le
(1 real change made)

. 
. gen date= date(str_date, "DMY", 2000) 
(1 missing value generated)

. format date %tdDDmonCCYY 

. replace date =. if date<td(24apr1999) | date>td(28apr1999) 
(773 real changes made, 773 to missing)

. 
. ** incumbent
. gen votinc=1 if P34==2
(1,862 missing values generated)

. replace votinc=0 if P34!=2 & P34!=.
(1,862 real changes made)

. label variable votinc "Vote for the incumbent"

. 
. 
. ** gender
. gen female=P38-1
(2 missing values generated)

. 
. 
. ** age
. gen age=P39
(3 missing values generated)

. 
. 
. ** education
. recode P40A (1=1) (2=2) (3=3) (4=4) (6=5) (5=6) (7=7) (8/11=8) (13=9) (12=10) (14 99=.), gen(edu)
(698 differences between P40A and edu)

. 
. 
. ** employment status
. recode P42 (1=1 "employed") (4 5 =2 "unemployed") (6=3 "student") (2 3 =4 "retired") (7=5 "housework") (8
>  9 =.), gen(emplo)  
(1,408 differences between P42 and emplo)

. 
. 
. ** size of municipality
. clonevar munsz=TAMUNI

. 
. 
. ** ccaa
. rename CCAA ccaa

. 
. 
. ** survey id
. gen studyid="0499"

. 
. 
. ** random treatment variable 
. preserve

. 
. bysort date: gen date_unique= _n ==1 

. replace date_unique=. if date==.
(774 real changes made, 774 to missing)

. keep if date_unique==1
(2,494 observations deleted)

. set seed 222

. sample 1, count 
(4 observations deleted)

. scalar random_attdate = date 

. 
. restore

. 
. display %tdDDmonCCYY random_attdate
27apr1999

. gen randdate= random_attdate // creating a variable with the random date

. format randdate %tdDDmonCCYY

. scalar drop random_attdate

. 
. gen randtreat = 1 if date>randdate & date!=. // creating a variable for the random treatment
(2,447 missing values generated)

. replace randtreat = 0 if date<randdate
(1,283 real changes made)

. replace randtreat = . if date==randdate
(0 real changes made)

. label variable randtreat "random treatment"

. label define treat 0 "pre" 1 "post"

. label values randtreat treat

. 
. 
. save "harmonized dataset\1999_04", replace  
(file harmonized dataset\1999_04.dta not found)
file harmonized dataset\1999_04.dta saved

. 
. 
. 
. 
. ***************************** JULY 1999 ****************************************
. 
. import spss using "CIS Studies\2367.sav", clear
(109 vars, 2,490 obs)

. 
. 
. ** date
. gen str_date= substr(FINAL,18,6) 

. tab str_date

   str_date |      Freq.     Percent        Cum.
------------+-----------------------------------
     080799 |         40        1.61        1.61
     090799 |        498       20.00       21.61
     100799 |        471       18.92       40.52
     110799 |        160        6.43       46.95
     120799 |        744       29.88       76.83
     130799 |        520       20.88       97.71
     140799 |         46        1.85       99.56
     150799 |          8        0.32       99.88
     170799 |          1        0.04       99.92
     190799 |          1        0.04       99.96
     999999 |          1        0.04      100.00
------------+-----------------------------------
      Total |      2,490      100.00

. replace str_date="" if str_date=="999999" // for this respondent, the date of the interview is not availa
> ble
(1 real change made)

. 
. gen date= date(str_date, "DMY", 2000) 
(1 missing value generated)

. format date %tdDDmonCCYY 

. replace date =. if date<td(09jul1999) | date>td(15jul1999) 
(42 real changes made, 42 to missing)

. 
. 
. ** incumbent
. gen votinc=1 if P25==2
(1,826 missing values generated)

. replace votinc=0 if P25!=2 & P25!=.
(1,823 real changes made)

. label variable votinc "Vote for the incumbent"

. 
. 
. ** gender
. gen female=P30-1

. 
. 
. ** age
. gen age=P31

. 
. 
. ** education
. recode P32A (1=1) (2=2) (3=3) (4=4) (6=5) (5=6) (7=7) (8/11=8) (13=9) (12=10) (14 99=.), gen(edu)
(675 differences between P32A and edu)

. 
. 
. ** employment status
. recode P34 (1=1 "employed") (4 5 =2 "unemployed") (6=3 "student") (2 3 =4 "retired") (7=5 "housework") (8
>  9 =.), gen(emplo)  
(1,412 differences between P34 and emplo)

. 
. 
. ** size of municipality
. clonevar munsz=TAMUNI

. 
. 
. ** ccaa
. rename CCAA ccaa

. 
. 
. ** survey id
. gen studyid="0799"

. 
. 
. ** random treatment variable 
. preserve

. 
. bysort date: gen date_unique= _n ==1 

. replace date_unique=. if date==.
(43 real changes made, 43 to missing)

. keep if date_unique==1
(2,483 observations deleted)

. set seed 2112

. sample 1, count 
(6 observations deleted)

. scalar random_attdate = date 

. 
. restore

. 
. display %tdDDmonCCYY random_attdate
11jul1999

. gen randdate= random_attdate // creating a variable with the random date

. format randdate %tdDDmonCCYY

. scalar drop random_attdate

. 
. gen randtreat = 1 if date>randdate & date!=. // creating a variable for the random treatment
(1,172 missing values generated)

. replace randtreat = 0 if date<randdate
(969 real changes made)

. replace randtreat = . if date==randdate
(0 real changes made)

. label variable randtreat "random treatment"

. label define treat 0 "pre" 1 "post"

. label values randtreat treat

. 
. 
. save "harmonized dataset\1999_07", replace 
(file harmonized dataset\1999_07.dta not found)
file harmonized dataset\1999_07.dta saved

. 
. 
. 
. 
. ***************************** OCTOBER 1999 *************************************
. 
. import spss using "CIS Studies\2372.sav", clear
(119 vars, 2,496 obs)

. 
. 
. ** date
. gen str_date= substr(FINAL,18,6)

. tab str_date

   str_date |      Freq.     Percent        Cum.
------------+-----------------------------------
         99 |          1        0.04        0.04
     041099 |          8        0.32        0.36
     051099 |         10        0.40        0.76
     061099 |          1        0.04        0.80
     131099 |          1        0.04        0.84
     141099 |          1        0.04        0.88
     211099 |         38        1.52        2.40
     221099 |        459       18.39       20.79
     231099 |        620       24.84       45.63
     241099 |        205        8.21       53.85
     251099 |        706       28.29       82.13
     261099 |        373       14.94       97.08
     271099 |         40        1.60       98.68
     281099 |         29        1.16       99.84
     291099 |          4        0.16      100.00
------------+-----------------------------------
      Total |      2,496      100.00

. replace str_date="" if str_date=="    99" // for this respondent, the day and the month of the interview 
> are not available
(1 real change made)

. 
. gen date= date(str_date, "DMY", 2000) 
(1 missing value generated)

. format date %tdDDmonCCYY 

. replace date =. if date<td(22oct1999) | date>td(26oct1999) 
(132 real changes made, 132 to missing)

. 
. 
. ** incumbent
. gen votinc=1 if P26==2
(1,851 missing values generated)

. replace votinc=0 if P26!=2 & P26!=.
(1,851 real changes made)

. label variable votinc "Vote for the incumbent"

. 
. 
. ** gender
. gen female=P31-1

. 
. 
. ** age
. gen age=P32

. replace age=. if age==99
(1 real change made, 1 to missing)

. 
. 
. ** education
. recode P33A (1=1) (2=2) (3=3) (4=4) (6=5) (5=6) (7=7) (8/11=8) (13=9) (12=10) (14 99=.), gen(edu)
(658 differences between P33A and edu)

. 
. 
. ** employment status
. recode P35 (1=1 "employed") (4 5 =2 "unemployed") (6=3 "student") (2 3 =4 "retired") (7=5 "housework") (8
>  9 =.), gen(emplo)   
(1,397 differences between P35 and emplo)

. 
. 
. ** size of municipality
. clonevar munsz=TAMUNI

. 
. 
. ** ccaa
. rename CCAA ccaa

. 
. 
. ** survey id
. gen studyid="1099"

. 
. 
. ** random treatment variable  
. preserve

. 
. bysort date: gen date_unique= _n ==1 

. replace date_unique=. if date==.
(133 real changes made, 133 to missing)

. keep if date_unique==1
(2,491 observations deleted)

. set seed 2222

. sample 1, count 
(4 observations deleted)

. scalar random_attdate = date 

. 
. restore

. 
. display %tdDDmonCCYY random_attdate
24oct1999

. gen randdate= random_attdate // creating a variable with the random date

. format randdate %tdDDmonCCYY

. scalar drop random_attdate

. 
. gen randtreat = 1 if date>randdate & date!=. // creating a variable for the random treatment
(1,417 missing values generated)

. replace randtreat = 0 if date<randdate
(1,079 real changes made)

. replace randtreat = . if date==randdate
(0 real changes made)

. label variable randtreat "random treatment"

. label define treat 0 "pre" 1 "post"

. label values randtreat treat

. 
. 
. save "harmonized dataset\1999_10", replace 
(file harmonized dataset\1999_10.dta not found)
file harmonized dataset\1999_10.dta saved

. 
. 
. 
. 
. 
. 
. /*******************************************************************************
>                                     MERGE
> *******************************************************************************/
. 
. use "harmonized dataset\1998_10", clear 

. 
. append using "harmonized dataset\1999_01" "harmonized dataset\1999_04" "harmonized dataset\1999_07" "harm
> onized dataset\1999_10" 
(variable P42 was byte, now int to accommodate using data's values)
(label treat already defined)
(label labels0 already defined)
(label labels1 already defined)
(label labels2 already defined)
(label labels3 already defined)
(label labels4 already defined)
(label labels5 already defined)
(label labels6 already defined)
(label labels7 already defined)
(label labels8 already defined)
(label labels9 already defined)
(label labels10 already defined)
(label labels11 already defined)
(label labels12 already defined)
(label labels13 already defined)
(label labels14 already defined)
(label labels15 already defined)
(label labels16 already defined)
(label labels17 already defined)
(label labels18 already defined)
(label labels19 already defined)
(label labels20 already defined)
(label labels21 already defined)
(label labels22 already defined)
(label labels23 already defined)
(label labels24 already defined)
(label labels25 already defined)
(label labels26 already defined)
(label labels27 already defined)
(label labels28 already defined)
(label labels29 already defined)
(label labels30 already defined)
(label labels31 already defined)
(label labels32 already defined)
(label labels33 already defined)
(label labels34 already defined)
(label labels35 already defined)
(label labels36 already defined)
(label labels37 already defined)
(label labels38 already defined)
(label labels39 already defined)
(label labels40 already defined)
(label labels41 already defined)
(label labels42 already defined)
(label labels43 already defined)
(label labels44 already defined)
(label labels45 already defined)
(label labels46 already defined)
(label labels47 already defined)
(label emplo already defined)
(label treat already defined)
(label labels0 already defined)
(label labels1 already defined)
(label labels2 already defined)
(label labels3 already defined)
(label labels4 already defined)
(label labels5 already defined)
(label labels6 already defined)
(label labels7 already defined)
(label labels8 already defined)
(label labels9 already defined)
(label labels10 already defined)
(label labels11 already defined)
(label labels12 already defined)
(label labels13 already defined)
(label labels14 already defined)
(label labels15 already defined)
(label labels16 already defined)
(label labels17 already defined)
(label labels18 already defined)
(label labels19 already defined)
(label labels20 already defined)
(label labels21 already defined)
(label labels22 already defined)
(label labels23 already defined)
(label labels24 already defined)
(label labels25 already defined)
(label labels26 already defined)
(label labels27 already defined)
(label labels28 already defined)
(label labels29 already defined)
(label labels30 already defined)
(label labels31 already defined)
(label labels32 already defined)
(label labels33 already defined)
(label labels34 already defined)
(label labels35 already defined)
(label labels36 already defined)
(label labels37 already defined)
(label labels38 already defined)
(label labels39 already defined)
(label labels40 already defined)
(label labels41 already defined)
(label labels42 already defined)
(label labels43 already defined)
(label labels44 already defined)
(label labels45 already defined)
(label labels46 already defined)
(label labels47 already defined)
(label emplo already defined)
(label treat already defined)
(label labels0 already defined)
(label labels1 already defined)
(label labels2 already defined)
(label labels3 already defined)
(label labels4 already defined)
(label labels5 already defined)
(label labels6 already defined)
(label labels7 already defined)
(label labels8 already defined)
(label labels9 already defined)
(label labels10 already defined)
(label labels11 already defined)
(label labels12 already defined)
(label labels13 already defined)
(label labels14 already defined)
(label labels15 already defined)
(label labels16 already defined)
(label labels17 already defined)
(label labels18 already defined)
(label labels19 already defined)
(label labels20 already defined)
(label labels21 already defined)
(label labels22 already defined)
(label labels23 already defined)
(label labels24 already defined)
(label labels25 already defined)
(label labels26 already defined)
(label labels27 already defined)
(label labels28 already defined)
(label labels29 already defined)
(label labels30 already defined)
(label labels31 already defined)
(label labels32 already defined)
(label labels33 already defined)
(label labels34 already defined)
(label labels35 already defined)
(label labels36 already defined)
(label labels37 already defined)
(label labels38 already defined)
(label labels39 already defined)
(label labels40 already defined)
(label labels41 already defined)
(label labels42 already defined)
(label labels43 already defined)
(label emplo already defined)
(variable P36 was byte, now int to accommodate using data's values)
(label treat already defined)
(label labels0 already defined)
(label labels1 already defined)
(label labels2 already defined)
(label labels3 already defined)
(label labels4 already defined)
(label labels5 already defined)
(label labels6 already defined)
(label labels7 already defined)
(label labels8 already defined)
(label labels9 already defined)
(label labels10 already defined)
(label labels11 already defined)
(label labels12 already defined)
(label labels13 already defined)
(label labels14 already defined)
(label labels15 already defined)
(label labels16 already defined)
(label labels17 already defined)
(label labels18 already defined)
(label labels19 already defined)
(label labels20 already defined)
(label labels21 already defined)
(label labels22 already defined)
(label labels23 already defined)
(label labels24 already defined)
(label labels25 already defined)
(label labels26 already defined)
(label labels27 already defined)
(label labels28 already defined)
(label labels29 already defined)
(label labels30 already defined)
(label labels31 already defined)
(label labels32 already defined)
(label labels33 already defined)
(label labels34 already defined)
(label labels35 already defined)
(label labels36 already defined)
(label labels37 already defined)
(label labels38 already defined)
(label labels39 already defined)
(label labels40 already defined)
(label labels41 already defined)
(label labels42 already defined)
(label labels43 already defined)
(label labels44 already defined)
(label labels45 already defined)
(label labels46 already defined)
(label emplo already defined)

. 
. keep date votinc female age edu emplo munsz ccaa studyid randtreat randdate

. encode studyid, gen(study) // study id

. drop studyid

. rename study studyid

. gen respid = _n // respondent id

. 
. 
. 
. ** random assignment of the region of the attack: we assign to each of the 5 surveys one of the 5 most re
> presented regions in the attacks used in the main study (i.e. Andalucía, Catalunya, Madrid, Navarra, País
>  Vasco - see Table A2)
. sort studyid respid

. by studyid: gen first = _n == 1 

. 
. preserve

. keep if first==1
(12,463 observations deleted)

. set seed 666

. gen random = runiform() 

. sort random 

. gen randreg = .
(5 missing values generated)

. replace randreg = 1 in 1 
(1 real change made)

. replace randreg = 9 in 2
(1 real change made)

. replace randreg = 13 in 3
(1 real change made)

. replace randreg = 15 in 4
(1 real change made)

. replace randreg = 16 in 5
(1 real change made)

. keep respid studyid randreg

. save "harmonized dataset\first0", replace
(file harmonized dataset\first0.dta not found)
file harmonized dataset\first0.dta saved

. restore

. 
. merge 1:1 studyid respid using "harmonized dataset\first0" 
(label study already defined)

    Result                      Number of obs
    -----------------------------------------
    Not matched                        12,463
        from master                    12,463  (_merge==1)
        from using                          0  (_merge==2)

    Matched                                 5  (_merge==3)
    -----------------------------------------

. label values randreg labels0

. drop first _merge

. rm "harmonized dataset\first0.dta"

. 
. bysort studyid: replace randreg = randreg[1] 
(12,463 real changes made)

. 
. 
. ** creating the dichotomous variable for the region of the attack   
. gen regattack = 1 if ccaa==randreg
(11,153 missing values generated)

. replace regattack = 0 if ccaa!=randreg
(11,153 real changes made)

. label variable regattack "attacked region"

. 
. 
. 
. save "harmonized dataset\allbar", replace // 5-study dataset
(file harmonized dataset\allbar.dta not found)
file harmonized dataset\allbar.dta saved

. 
. 
. 
. 
. 
. 
. /*******************************************************************************
>                             CREATION OF X20 DATASET
> *******************************************************************************/
. 
. use "harmonized dataset\allbar", clear 

. 
. 
. forval i = 1/19 {
  2.     append using "harmonized dataset\allbar"
  3. } 
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)
(label study already defined)
(label emplo already defined)
(label labels2 already defined)
(label labels0 already defined)
(label treat already defined)

. 
. 
. ** creating an identifier for each of the 100 surveys in the dataset
. local n_obs_per_repetition = _N / 20 

. display `n_obs_per_repetition'
12468

. 
. gen repetition = floor((_n - 1) / `n_obs_per_repetition') + 1  

. 
. sort studyid repetition

. egen surid= group(studyid repetition) // survey id

. 
. 
. 
. ** creating, for each of the surveys, a random date variable. 
. bysort surid: egen min_date = min(date) 

. bysort surid: egen max_date = max(date) 

. 
. set seed 777

. gen random_number = runiform() 

. bysort surid: replace random_number = random_number[1] 
(249,260 real changes made)

. bysort surid: egen randdate100 = min(min_date + random_number * (max_date - min_date)) 

. replace randdate100 = floor(randdate100) 
(249,360 real changes made)

. format randdate100 %tdDDmonCCYY

. drop random_number min_date max_date

. 
. 
. 
. ** creating, for each of the surveys, random treatment variables based on the random date variable 
. gen randtreat100 = 1 if date>randdate100 & date!=. 
(132,696 missing values generated)

. replace randtreat100 = 0 if date<randdate100 
(64,785 real changes made)

. replace randtreat100 = . if date==randdate100
(0 real changes made)

. label variable randtreat100 "random treatment for the 100 surveys"

. label values randtreat100 treat

. 
. 
. 
. ** randomly assigning the region of the attack, mirroring the distribution of regions in the attacks used
>  in the main analysis (see Table A2)
. sort surid respid

. by surid: gen first = _n == 1 

. 
. preserve

. keep if first==1
(249,260 observations deleted)

. set seed 888

. gen random = runiform() 

. sort random 

. gen randreg100 = .
(100 missing values generated)

. replace randreg100 = 1 in 1/6 
(6 real changes made)

. replace randreg100 = 2 in 7/8
(2 real changes made)

. replace randreg100 = 16 in 9/56
(48 real changes made)

. replace randreg100 = 6 in 57
(1 real change made)

. replace randreg100 = 8 in 58/59
(2 real changes made)

. replace randreg100 = 9 in 60/65
(6 real changes made)

. replace randreg100 = 12 in 66/68
(3 real changes made)

. replace randreg100 = 17 in 69
(1 real change made)

. replace randreg100 = 13 in 70/94
(25 real changes made)

. replace randreg100 = 15 in 95/99
(5 real changes made)

. replace randreg100 = 10 in 100
(1 real change made)

. keep respid surid randreg100

. save "harmonized dataset\first", replace
(file harmonized dataset\first.dta not found)
file harmonized dataset\first.dta saved

. restore

. 
. merge 1:1 surid respid using "harmonized dataset\first" 

    Result                      Number of obs
    -----------------------------------------
    Not matched                       249,260
        from master                   249,260  (_merge==1)
        from using                          0  (_merge==2)

    Matched                               100  (_merge==3)
    -----------------------------------------

. label values randreg100 labels0

. drop first _merge

. rm "harmonized dataset\first.dta"

. 
. bysort surid: replace randreg100 = randreg100[1] 
(249,260 real changes made)

. 
. 
. 
. ** creating the dichotomous variable for the region of the attack   
. gen regattack100 = 1 if ccaa==randreg100
(228,236 missing values generated)

. replace regattack100 = 0 if ccaa!=randreg100
(228,236 real changes made)

. label variable regattack100 "attacked region"

. 
. 
. 
. 
. ** "eliminating" UESDs with only "pre" or only "post" observations 
. bysort surid: egen n_pre = total(randtreat100 == 0) 

. bysort surid: egen n_post = total(randtreat100 == 1) 

. gen tag = 0

. replace tag = 1 if n_pre == 0 | n_post == 0 
(49,878 real changes made)

. replace randtreat100=. if tag==1 
(37,105 real changes made, 37,105 to missing)

. drop n_pre n_post tag

. 
. 
. 
. save "harmonized dataset\allbar20", replace
(file harmonized dataset\allbar20.dta not found)
file harmonized dataset\allbar20.dta saved

. 
. 
. 
. 
. /*******************************************************************************
>                          MODELS FOR THE MERGED (5-SURVEY) DATASET
> *******************************************************************************/
. 
. use "harmonized dataset\allbar", clear

. 
. ** needed for the balance tests
. tabulate emplo, gen(em)

  RECODE of |
        P42 |      Freq.     Percent        Cum.
------------+-----------------------------------
   employed |      5,225       42.18       42.18
 unemployed |      1,208        9.75       51.94
    student |        958        7.73       59.67
    retired |      2,712       21.90       81.57
  housework |      2,283       18.43      100.00
------------+-----------------------------------
      Total |     12,386      100.00

. tabulate munsz, gen(mu)

            Tamaño de habitat |      Freq.     Percent        Cum.
------------------------------+-----------------------------------
     Menos de 2000 habitantes |        999        8.01        8.01
    2.001 a 10.000 habitantes |      2,016       16.17       24.18
   10.001 a 50.000 habitantes |      2,957       23.72       47.90
  50.001 a 100.000 habitantes |      1,197        9.60       57.50
   100001 a 400000 habitantes |      2,983       23.93       81.42
400001 a 1.000.000 habitantes |        824        6.61       88.03
  Más de 1.000.000 habitantes |      1,492       11.97      100.00
------------------------------+-----------------------------------
                        Total |     12,468      100.00

. 
. 
. ** balance tests
. reg female i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     9,031
-------------+----------------------------------   F(7, 9023)      =      0.36
       Model |  .633591065         7  .090513009   Prob > F        =    0.9243
    Residual |  2253.82151     9,023  .249786269   R-squared       =    0.0003
-------------+----------------------------------   Adj R-squared   =   -0.0005
       Total |   2254.4551     9,030  .249662802   Root MSE        =    .49979

-------------------------------------------------------------------------------------
             female | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |  -.0006923   .0125697    -0.06   0.956    -.0253318    .0239471
        1.regattack |   .0116834   .0233164     0.50   0.616    -.0340219    .0573888
                    |
randtreat#regattack |
            post#1  |   -.033297   .0356544    -0.93   0.350    -.1031877    .0365936
                    |
            studyid |
              0499  |   .0210076   .0214841     0.98   0.328    -.0211061    .0631213
              0799  |   .0125772   .0173752     0.72   0.469    -.0214822    .0466366
              1098  |   .0097105   .0190452     0.51   0.610    -.0276223    .0470434
              1099  |   .0093165   .0178392     0.52   0.602    -.0256523    .0442853
                    |
              _cons |   .5090621   .0170091    29.93   0.000     .4757204    .5424039
-------------------------------------------------------------------------------------

. 
. reg age i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     9,025
-------------+----------------------------------   F(7, 9017)      =      0.39
       Model |  909.142284         7  129.877469   Prob > F        =    0.9110
    Residual |  3032478.15     9,017  336.306771   R-squared       =    0.0003
-------------+----------------------------------   Adj R-squared   =   -0.0005
       Total |   3033387.3     9,024  336.146642   Root MSE        =    18.339

-------------------------------------------------------------------------------------
                age | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |  -.0810507   .4613877    -0.18   0.861    -.9854753     .823374
        1.regattack |  -1.188766   .8556229    -1.39   0.165    -2.865981    .4884494
                    |
randtreat#regattack |
            post#1  |   .5289214   1.309242     0.40   0.686    -2.037491    3.095333
                    |
            studyid |
              0499  |   .1840757   .7887809     0.23   0.815    -1.362114    1.730266
              0799  |   .1620148   .6380172     0.25   0.800    -1.088644    1.412673
              1098  |   .3033376   .6994037     0.43   0.665    -1.067653    1.674328
              1099  |  -.1301056   .6550368    -0.20   0.843    -1.414126    1.153915
                    |
              _cons |   45.19683   .6247328    72.35   0.000     43.97221    46.42145
-------------------------------------------------------------------------------------

. 
. reg edu i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     8,218
-------------+----------------------------------   F(7, 8210)      =      2.64
       Model |  90.9856388         7  12.9979484   Prob > F        =    0.0101
    Residual |  40445.6276     8,210  4.92638583   R-squared       =    0.0022
-------------+----------------------------------   Adj R-squared   =    0.0014
       Total |  40536.6133     8,217  4.93326193   Root MSE        =    2.2195

-------------------------------------------------------------------------------------
                edu | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |  -.1103671   .0582643    -1.89   0.058      -.22458    .0038457
        1.regattack |   .2820359   .1095594     2.57   0.010     .0672718       .4968
                    |
randtreat#regattack |
            post#1  |   -.025528   .1668594    -0.15   0.878    -.3526146    .3015586
                    |
            studyid |
              0499  |  -.1272689   .1000493    -1.27   0.203    -.3233909    .0688531
              0799  |   -.067635   .0807994    -0.84   0.403    -.2260222    .0907522
              1098  |  -.2243791   .0886034    -2.53   0.011    -.3980642   -.0506941
              1099  |  -.0870579   .0827625    -1.05   0.293    -.2492934    .0751776
                    |
              _cons |   4.080815   .0789926    51.66   0.000     3.925969    4.235661
-------------------------------------------------------------------------------------

. 
. reg em1 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     8,972
-------------+----------------------------------   F(7, 8964)      =      4.35
       Model |  7.42519776         7  1.06074254   Prob > F        =    0.0001
    Residual |  2187.90249     8,964  .244076583   R-squared       =    0.0034
-------------+----------------------------------   Adj R-squared   =    0.0026
       Total |  2195.32769     8,971  .244713821   Root MSE        =    .49404

-------------------------------------------------------------------------------------
                em1 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |  -.0105582   .0124722    -0.85   0.397    -.0350064    .0138901
        1.regattack |  -.0233338   .0230944    -1.01   0.312    -.0686042    .0219366
                    |
randtreat#regattack |
            post#1  |   .0912359   .0354111     2.58   0.010     .0218221    .1606497
                    |
            studyid |
              0499  |  -.0051963   .0212982    -0.24   0.807    -.0469457    .0365531
              0799  |  -.0041369   .0172385    -0.24   0.810    -.0379283    .0296545
              1098  |  -.0629382   .0188994    -3.33   0.001    -.0999853    -.025891
              1099  |   .0037002   .0177016     0.21   0.834    -.0309991    .0383994
                    |
              _cons |   .4445891   .0168792    26.34   0.000      .411502    .4776762
-------------------------------------------------------------------------------------

. reg em2 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     8,972
-------------+----------------------------------   F(7, 8964)      =      3.94
       Model |  2.39881325         7  .342687608   Prob > F        =    0.0003
    Residual |  780.012689     8,964  .087016141   R-squared       =    0.0031
-------------+----------------------------------   Adj R-squared   =    0.0023
       Total |  782.411502     8,971   .08721564   Root MSE        =    .29498

-------------------------------------------------------------------------------------
                em2 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |   .0114261    .007447     1.53   0.125    -.0031716    .0260238
        1.regattack |   .0391885   .0137894     2.84   0.004     .0121582    .0662188
                    |
randtreat#regattack |
            post#1  |  -.0315313   .0211434    -1.49   0.136    -.0729773    .0099147
                    |
            studyid |
              0499  |   .0117981   .0127169     0.93   0.354    -.0131299    .0367261
              0799  |   .0040412   .0102929     0.39   0.695    -.0161352    .0242176
              1098  |   .0366015   .0112846     3.24   0.001     .0144812    .0587218
              1099  |   .0079911   .0105694     0.76   0.450    -.0127274    .0287095
                    |
              _cons |   .0764049   .0100783     7.58   0.000      .056649    .0961607
-------------------------------------------------------------------------------------

. reg em3 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     8,972
-------------+----------------------------------   F(7, 8964)      =      0.63
       Model |  .310609909         7  .044372844   Prob > F        =    0.7274
    Residual |  626.453991     8,964  .069885541   R-squared       =    0.0005
-------------+----------------------------------   Adj R-squared   =   -0.0003
       Total |  626.764601     8,971  .069865634   Root MSE        =    .26436

-------------------------------------------------------------------------------------
                em3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |   -.009839   .0066738    -1.47   0.140    -.0229211    .0032432
        1.regattack |   .0029268   .0123577     0.24   0.813    -.0212971    .0271507
                    |
randtreat#regattack |
            post#1  |  -.0038424   .0189483    -0.20   0.839    -.0409854    .0333005
                    |
            studyid |
              0499  |  -.0045728   .0113966    -0.40   0.688    -.0269127    .0177671
              0799  |  -.0044853   .0092242    -0.49   0.627    -.0225669    .0135963
              1098  |  -.0123261    .010113    -1.22   0.223    -.0321499    .0074976
              1099  |  -.0104286    .009472    -1.10   0.271     -.028996    .0081388
                    |
              _cons |   .0867385    .009032     9.60   0.000     .0690338    .1044432
-------------------------------------------------------------------------------------

. reg em4 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     8,972
-------------+----------------------------------   F(7, 8964)      =      1.18
       Model |  1.40397429         7  .200567756   Prob > F        =    0.3086
    Residual |  1519.68062     8,964  .169531529   R-squared       =    0.0009
-------------+----------------------------------   Adj R-squared   =    0.0001
       Total |   1521.0846     8,971  .169555746   Root MSE        =    .41174

-------------------------------------------------------------------------------------
                em4 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |   .0181376   .0103945     1.74   0.081    -.0022381    .0385132
        1.regattack |  -.0164247   .0192473    -0.85   0.393    -.0541538    .0213044
                    |
randtreat#regattack |
            post#1  |  -.0241363   .0295122    -0.82   0.413    -.0819869    .0337143
                    |
            studyid |
              0499  |   .0213236   .0177503     1.20   0.230     -.013471    .0561183
              0799  |    .014522   .0143669     1.01   0.312    -.0136403    .0426844
              1098  |   .0297233   .0157511     1.89   0.059    -.0011524     .060599
              1099  |   .0158096   .0147528     1.07   0.284    -.0131094    .0447285
                    |
              _cons |   .1939804   .0140674    13.79   0.000     .1664051    .2215558
-------------------------------------------------------------------------------------

. reg em5 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     8,972
-------------+----------------------------------   F(7, 8964)      =      1.51
       Model |  1.58676154         7   .22668022   Prob > F        =    0.1596
    Residual |  1348.12735     8,964  .150393502   R-squared       =    0.0012
-------------+----------------------------------   Adj R-squared   =    0.0004
       Total |  1349.71411     8,971  .150453028   Root MSE        =    .38781

-------------------------------------------------------------------------------------
                em5 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |  -.0091666   .0097902    -0.94   0.349    -.0283577    .0100245
        1.regattack |  -.0023568   .0181284    -0.13   0.897    -.0378926    .0331789
                    |
randtreat#regattack |
            post#1  |  -.0317258   .0277965    -1.14   0.254    -.0862134    .0227617
                    |
            studyid |
              0499  |  -.0233527   .0167184    -1.40   0.163    -.0561246    .0094193
              0799  |  -.0099411   .0135317    -0.73   0.463    -.0364662    .0165841
              1098  |   .0089395   .0148354     0.60   0.547    -.0201413    .0380202
              1099  |  -.0170722   .0138952    -1.23   0.219      -.04431    .0101655
                    |
              _cons |   .1982871   .0132496    14.97   0.000     .1723149    .2242594
-------------------------------------------------------------------------------------

. 
. reg mu1 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     9,032
-------------+----------------------------------   F(7, 9024)      =      5.46
       Model |    2.977681         7     .425383   Prob > F        =    0.0000
    Residual |  703.036491     9,024  .077907413   R-squared       =    0.0042
-------------+----------------------------------   Adj R-squared   =    0.0034
       Total |  706.014172     9,031  .078176744   Root MSE        =    .27912

-------------------------------------------------------------------------------------
                mu1 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |  -.0113461   .0070199    -1.62   0.106    -.0251066    .0024144
        1.regattack |  -.0567446   .0130216    -4.36   0.000    -.0822698   -.0312193
                    |
randtreat#regattack |
            post#1  |   .0147994   .0199121     0.74   0.457    -.0242328    .0538317
                    |
            studyid |
              0499  |  -.0086074   .0119967    -0.72   0.473    -.0321236    .0149088
              0799  |  -.0129403   .0097037    -1.33   0.182    -.0319617    .0060811
              1098  |    .013152   .0106363     1.24   0.216    -.0076975    .0340016
              1099  |  -.0172169   .0099628    -1.73   0.084    -.0367462    .0023124
                    |
              _cons |   .1015458   .0094992    10.69   0.000     .0829252    .1201664
-------------------------------------------------------------------------------------

. reg mu2 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     9,032
-------------+----------------------------------   F(7, 9024)      =      7.91
       Model |  7.85429009         7  1.12204144   Prob > F        =    0.0000
    Residual |  1280.73904     9,024  .141925869   R-squared       =    0.0061
-------------+----------------------------------   Adj R-squared   =    0.0053
       Total |  1288.59333     9,031  .142685565   Root MSE        =    .37673

-------------------------------------------------------------------------------------
                mu2 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |   .0041562   .0094748     0.44   0.661    -.0144166     .022729
        1.regattack |  -.0379027   .0175754    -2.16   0.031    -.0723544   -.0034509
                    |
randtreat#regattack |
            post#1  |   .0771298   .0268756     2.87   0.004     .0244475    .1298121
                    |
            studyid |
              0499  |  -.0649116    .016192    -4.01   0.000    -.0966516   -.0331715
              0799  |  -.0818123   .0130972    -6.25   0.000    -.1074857   -.0561389
              1098  |  -.0509595   .0143559    -3.55   0.000    -.0791004   -.0228186
              1099  |    -.05402   .0134469    -4.02   0.000    -.0803789   -.0276611
                    |
              _cons |    .225045   .0128212    17.55   0.000     .1999126    .2501775
-------------------------------------------------------------------------------------

. reg mu3 i.randtreat##i.regattack i.studyid  

      Source |       SS           df       MS      Number of obs   =     9,032
-------------+----------------------------------   F(7, 9024)      =      4.44
       Model |  5.59219026         7  .798884322   Prob > F        =    0.0001
    Residual |  1622.09382     9,024  .179753304   R-squared       =    0.0034
-------------+----------------------------------   Adj R-squared   =    0.0027
       Total |  1627.68601     9,031  .180233197   Root MSE        =    .42397

-------------------------------------------------------------------------------------
                mu3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |   .0025506    .010663     0.24   0.811    -.0183513    .0234524
        1.regattack |   .0131808   .0197794     0.67   0.505    -.0255913    .0519529
                    |
randtreat#regattack |
            post#1  |   -.117842   .0302459    -3.90   0.000    -.1771308   -.0585533
                    |
            studyid |
              0499  |   .0283919   .0182226     1.56   0.119    -.0073285    .0641122
              0799  |   .0296905   .0147396     2.01   0.044     .0007976    .0585834
              1098  |   .0028824   .0161562     0.18   0.858    -.0287874    .0345522
              1099  |    .023982   .0151331     1.58   0.113    -.0056824    .0536464
                    |
              _cons |    .220167    .014429    15.26   0.000     .1918829    .2484511
-------------------------------------------------------------------------------------

. reg mu4 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     9,032
-------------+----------------------------------   F(7, 9024)      =      2.12
       Model |  1.22771597         7  .175387995   Prob > F        =    0.0383
    Residual |  746.780145     9,024  .082754892   R-squared       =    0.0016
-------------+----------------------------------   Adj R-squared   =    0.0009
       Total |  748.007861     9,031  .082826693   Root MSE        =    .28767

-------------------------------------------------------------------------------------
                mu4 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |   .0183615    .007235     2.54   0.011     .0041793    .0325436
        1.regattack |  -.0075779   .0134206    -0.56   0.572    -.0338853    .0187295
                    |
randtreat#regattack |
            post#1  |  -.0224378   .0205222    -1.09   0.274     -.062666    .0177904
                    |
            studyid |
              0499  |   .0335197   .0123643     2.71   0.007      .009283    .0577565
              0799  |   .0164254    .010001     1.64   0.101    -.0031788    .0360296
              1098  |   .0140844   .0109622     1.28   0.199    -.0074039    .0355728
              1099  |   .0184013    .010268     1.79   0.073    -.0017264     .038529
                    |
              _cons |   .0680862   .0097903     6.95   0.000      .048895    .0872773
-------------------------------------------------------------------------------------

. reg mu5 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     9,032
-------------+----------------------------------   F(7, 9024)      =      5.15
       Model |  6.56101793         7  .937288276   Prob > F        =    0.0000
    Residual |  1643.63905     9,024  .182140852   R-squared       =    0.0040
-------------+----------------------------------   Adj R-squared   =    0.0032
       Total |  1650.20007     9,031  .182726173   Root MSE        =    .42678

-------------------------------------------------------------------------------------
                mu5 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |  -.0081249   .0107335    -0.76   0.449    -.0291651    .0129153
        1.regattack |   .0296303   .0199103     1.49   0.137    -.0093985     .068659
                    |
randtreat#regattack |
            post#1  |   -.145115   .0304461    -4.77   0.000    -.2047962   -.0854338
                    |
            studyid |
              0499  |   .0082519   .0183432     0.45   0.653    -.0277049    .0442087
              0799  |    .024826   .0148371     1.67   0.094    -.0042582    .0539101
              1098  |   .0113154   .0162631     0.70   0.487     -.020564    .0431949
              1099  |   .0151286   .0152333     0.99   0.321    -.0147321    .0449894
                    |
              _cons |   .2337569   .0145245    16.09   0.000     .2052856    .2622282
-------------------------------------------------------------------------------------

. reg mu6 i.randtreat##i.regattack i.studyid 

      Source |       SS           df       MS      Number of obs   =     9,032
-------------+----------------------------------   F(7, 9024)      =      3.19
       Model |  1.48794528         7  .212563611   Prob > F        =    0.0022
    Residual |  600.877754     9,024  .066586631   R-squared       =    0.0025
-------------+----------------------------------   Adj R-squared   =    0.0017
       Total |    602.3657     9,031  .066699779   Root MSE        =    .25804

-------------------------------------------------------------------------------------
                mu6 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |   .0136404   .0064898     2.10   0.036     .0009188    .0263619
        1.regattack |   .0372786   .0120384     3.10   0.002     .0136806    .0608765
                    |
randtreat#regattack |
            post#1  |  -.0816487   .0184086    -4.44   0.000    -.1177337   -.0455636
                    |
            studyid |
              0499  |    .006966   .0110908     0.63   0.530    -.0147746    .0287066
              0799  |   .0001879    .008971     0.02   0.983    -.0173973    .0177731
              1098  |   .0051369   .0098332     0.52   0.601    -.0141384    .0244122
              1099  |  -.0052387   .0092105    -0.57   0.570    -.0232934     .012816
                    |
              _cons |    .064454    .008782     7.34   0.000     .0472394    .0816686
-------------------------------------------------------------------------------------

. reg mu7 i.randtreat##i.regattack i.studyid  

      Source |       SS           df       MS      Number of obs   =     9,032
-------------+----------------------------------   F(7, 9024)      =     49.62
       Model |  30.8603125         7  4.40861607   Prob > F        =    0.0000
    Residual |  801.791592     9,024  .088851019   R-squared       =    0.0371
-------------+----------------------------------   Adj R-squared   =    0.0363
       Total |  832.651904     9,031  .092199303   Root MSE        =    .29808

-------------------------------------------------------------------------------------
                mu7 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------+----------------------------------------------------------------
          randtreat |
              post  |  -.0192376   .0074967    -2.57   0.010    -.0339329   -.0045424
        1.regattack |   .0221355   .0139061     1.59   0.111    -.0051236    .0493947
                    |
randtreat#regattack |
            post#1  |   .2751142   .0212647    12.94   0.000     .2334306    .3167978
                    |
            studyid |
              0499  |  -.0036105   .0128116    -0.28   0.778    -.0287241    .0215031
              0799  |   .0236228   .0103628     2.28   0.023     .0033093    .0439362
              1098  |   .0043883   .0113588     0.39   0.699    -.0178775    .0266541
              1099  |   .0189636   .0106395     1.78   0.075    -.0018923    .0398194
                    |
              _cons |   .0869451   .0101445     8.57   0.000     .0670597    .1068305
-------------------------------------------------------------------------------------

. 
. 
. 
. 
. ** main effect & interaction models (TABLE D6)
. eststo clear 

. 
. eststo bas: reg votinc i.randtreat i.ccaa i.studyid

      Source |       SS           df       MS      Number of obs   =     9,028
-------------+----------------------------------   F(21, 9006)     =     19.50
       Model |  76.3332373        21  3.63491606   Prob > F        =    0.0000
    Residual |  1678.60196     9,006  .186387071   R-squared       =    0.0435
-------------+----------------------------------   Adj R-squared   =    0.0413
       Total |   1754.9352     9,027  .194409571   Root MSE        =    .43173

---------------------------------------------------------------------------------------
               votinc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
            randtreat |
                post  |   .0051989   .0106119     0.49   0.624    -.0156028    .0260007
                      |
                 ccaa |
              Aragón  |   .0532979   .0253748     2.10   0.036     .0035574    .1030384
            Asturias  |  -.0489362   .0298315    -1.64   0.101    -.1074128    .0095403
            Baleares  |   .0512817   .0376808     1.36   0.174    -.0225812    .1251445
            Canarias  |   .0477834    .024586     1.94   0.052    -.0004107    .0959776
           Cantabria  |   .0689192   .0376091     1.83   0.067    -.0048032    .1426417
  Castilla-la Mancha  |   .0625155   .0242041     2.58   0.010     .0150699    .1099611
       Castilla-León  |   .1227602   .0198214     6.19   0.000     .0839058    .1616146
            Cataluña  |  -.1039366   .0156776    -6.63   0.000    -.1346683   -.0732049
Comunidad Valenciana  |   .1392071   .0181926     7.65   0.000     .1035455    .1748687
          E5remadura  |   .1237825   .0285458     4.34   0.000     .0678262    .1797388
             Galicia  |   .0610427   .0206409     2.96   0.003     .0205818    .1015036
              Madrid  |   .0796699   .0171255     4.65   0.000        .0461    .1132398
              Murcia  |   .1484694   .0301885     4.92   0.000     .0892931    .2076458
             Navarra  |   .0012919   .0438717     0.03   0.977    -.0847066    .0872904
          País Vasco  |  -.1768598    .021906    -8.07   0.000    -.2198005   -.1339191
               Rioja  |   .0758104   .0569386     1.33   0.183    -.0358022    .1874231
                      |
              studyid |
                0499  |  -.0352073    .018673    -1.89   0.059    -.0718106    .0013961
                0799  |   -.012772    .015106    -0.85   0.398    -.0423831    .0168391
                1098  |  -.0149544   .0165217    -0.91   0.365    -.0473406    .0174318
                1099  |  -.0139956   .0154347    -0.91   0.365    -.0442511    .0162598
                      |
                _cons |   .2522778   .0170936    14.76   0.000     .2187704    .2857852
---------------------------------------------------------------------------------------

. estadd local controls "No"

added macro:
           e(controls) : "No"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "No"

added macro:
                e(imb) : "No"

. estadd local n = e(N)

added macro:
                  e(n) : "9028"

. 
. eststo bascon: reg votinc i.randtreat female c.age##c.age edu i.emplo i.munsz i.ccaa i.studyid 

      Source |       SS           df       MS      Number of obs   =     8,159
-------------+----------------------------------   F(35, 8123)     =     15.44
       Model |  99.9334685        35  2.85524196   Prob > F        =    0.0000
    Residual |  1502.23714     8,123  .184936248   R-squared       =    0.0624
-------------+----------------------------------   Adj R-squared   =    0.0583
       Total |  1602.17061     8,158  .196392573   Root MSE        =    .43004

------------------------------------------------------------------------------------------------
                        votinc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------------------+----------------------------------------------------------------
                     randtreat |
                         post  |   .0124613   .0111289     1.12   0.263    -.0093541    .0342767
                        female |  -.0269196   .0108678    -2.48   0.013    -.0482233   -.0056159
                           age |   .0007655   .0017286     0.44   0.658    -.0026229    .0041539
                               |
                   c.age#c.age |    .000015   .0000182     0.82   0.411    -.0000207    .0000507
                               |
                           edu |   .0165993   .0025427     6.53   0.000     .0116149    .0215837
                               |
                         emplo |
                   unemployed  |   .0042929   .0170158     0.25   0.801    -.0290624    .0376482
                      student  |    .015765   .0208214     0.76   0.449    -.0250503    .0565802
                      retired  |   .0485706   .0194919     2.49   0.013     .0103615    .0867797
                    housework  |   .0457918   .0163867     2.79   0.005     .0136697    .0779138
                               |
                         munsz |
    2.001 a 10.000 habitantes  |  -.0764539   .0209981    -3.64   0.000    -.1176156   -.0352922
   10.001 a 50.000 habitantes  |  -.0744564   .0204089    -3.65   0.000     -.114463   -.0344497
  50.001 a 100.000 habitantes  |  -.0554469    .023505    -2.36   0.018    -.1015227    -.009371
   100001 a 400000 habitantes  |  -.0350385   .0204814    -1.71   0.087    -.0751873    .0051102
400001 a 1.000.000 habitantes  |  -.0571979     .02622    -2.18   0.029    -.1085957      -.0058
  Más de 1.000.000 habitantes  |  -.0550433   .0263188    -2.09   0.037    -.1066349   -.0034517
                               |
                          ccaa |
                       Aragón  |   .0069272   .0273307     0.25   0.800     -.046648    .0605023
                     Asturias  |  -.0948282   .0308971    -3.07   0.002    -.1553943    -.034262
                     Baleares  |   .0249476   .0390513     0.64   0.523     -.051603    .1014982
                     Canarias  |   .0318801    .027276     1.17   0.243    -.0215878     .085348
                    Cantabria  |   .0218621   .0386397     0.57   0.572    -.0538816    .0976059
           Castilla-la Mancha  |   .0395359   .0271144     1.46   0.145    -.0136153     .092687
                Castilla-León  |   .0617751   .0217678     2.84   0.005     .0191045    .1044456
                     Cataluña  |  -.1408624   .0179109    -7.86   0.000    -.1759725   -.1057524
         Comunidad Valenciana  |   .1200489   .0193338     6.21   0.000     .0821496    .1579482
                   E5remadura  |   .0980685   .0322111     3.04   0.002     .0349265    .1612105
                      Galicia  |   .0280565   .0221829     1.26   0.206    -.0154277    .0715407
                       Madrid  |    .032284   .0219787     1.47   0.142       -.0108    .0753679
                       Murcia  |   .1470949    .033127     4.44   0.000     .0821574    .2120324
                      Navarra  |  -.0601371   .0446938    -1.35   0.178    -.1477484    .0274741
                   País Vasco  |  -.2251139   .0233079    -9.66   0.000    -.2708034   -.1794244
                        Rioja  |   .0334792    .058984     0.57   0.570    -.0821446     .149103
                               |
                       studyid |
                         0499  |  -.0387434   .0196246    -1.97   0.048    -.0772126   -.0002742
                         0799  |  -.0108123   .0158771    -0.68   0.496    -.0419355    .0203108
                         1098  |  -.0144559   .0173868    -0.83   0.406    -.0485385    .0196267
                         1099  |  -.0139475   .0161557    -0.86   0.388    -.0456168    .0177218
                               |
                         _cons |    .201833   .0488386     4.13   0.000      .106097    .2975691
------------------------------------------------------------------------------------------------

. estadd local controls "Yes"

added macro:
           e(controls) : "Yes"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "No"

added macro:
                e(imb) : "No"

. estadd local n = e(N)

added macro:
                  e(n) : "8159"

. 
. eststo basint: reg votinc i.randtreat##i.regattack i.ccaa i.studyid 

      Source |       SS           df       MS      Number of obs   =     9,028
-------------+----------------------------------   F(23, 9004)     =     17.92
       Model |  76.8260178        23  3.34026164   Prob > F        =    0.0000
    Residual |  1678.10918     9,004  .186373743   R-squared       =    0.0438
-------------+----------------------------------   Adj R-squared   =    0.0413
       Total |   1754.9352     9,027  .194409571   Root MSE        =    .43171

---------------------------------------------------------------------------------------
               votinc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
            randtreat |
                post  |   .0104406   .0111212     0.94   0.348    -.0113596    .0322407
          1.regattack |   .0177537   .0213107     0.83   0.405      -.02402    .0595274
                      |
  randtreat#regattack |
              post#1  |  -.0508515   .0315971    -1.61   0.108     -.112789     .011086
                      |
                 ccaa |
              Aragón  |   .0547664   .0256673     2.13   0.033     .0044527      .10508
            Asturias  |  -.0483684   .0300438    -1.61   0.107     -.107261    .0105242
            Baleares  |   .0538938   .0379129     1.42   0.155    -.0204242    .1282118
            Canarias  |   .0484657   .0248474     1.95   0.051    -.0002409    .0971723
           Cantabria  |   .0701742   .0378008     1.86   0.063    -.0039239    .1442723
  Castilla-la Mancha  |   .0638179   .0244917     2.61   0.009     .0158085    .1118272
       Castilla-León  |   .1242622   .0201939     6.15   0.000     .0846776    .1638467
            Cataluña  |  -.1006406   .0159315    -6.32   0.000      -.13187   -.0694113
Comunidad Valenciana  |   .1408163    .018611     7.57   0.000     .1043346    .1772981
          E5remadura  |   .1250099   .0287875     4.34   0.000     .0685798    .1814399
             Galicia  |   .0625554   .0210044     2.98   0.003      .021382    .1037289
              Madrid  |   .0839474   .0173278     4.84   0.000      .049981    .1179139
              Murcia  |   .1489076   .0304049     4.90   0.000     .0893071     .208508
             Navarra  |   .0006898   .0439146     0.02   0.987    -.0853928    .0867725
          País Vasco  |  -.1790657   .0219608    -8.15   0.000    -.2221139   -.1360174
               Rioja  |    .074694   .0570526     1.31   0.190     -.037142      .18653
                      |
              studyid |
                0499  |  -.0344042   .0187071    -1.84   0.066    -.0710745     .002266
                0799  |  -.0124394    .015107    -0.82   0.410    -.0420525    .0171738
                1098  |  -.0153291   .0165777    -0.92   0.355    -.0478251    .0171669
                1099  |  -.0147096   .0155072    -0.95   0.343    -.0451073    .0156881
                      |
                _cons |   .2488052   .0177518    14.02   0.000     .2140076    .2836027
---------------------------------------------------------------------------------------

. estadd local controls "No"

added macro:
           e(controls) : "No"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "No"

added macro:
                e(imb) : "No"

. estadd local n = e(N)

added macro:
                  e(n) : "9028"

. 
. eststo basinccon: reg votinc i.randtreat##i.regattack female c.age##c.age edu i.emplo i.munsz i.ccaa i.st
> udyid 

      Source |       SS           df       MS      Number of obs   =     8,159
-------------+----------------------------------   F(37, 8121)     =     14.69
       Model |  100.519654        37  2.71674739   Prob > F        =    0.0000
    Residual |  1501.65096     8,121  .184909612   R-squared       =    0.0627
-------------+----------------------------------   Adj R-squared   =    0.0585
       Total |  1602.17061     8,158  .196392573   Root MSE        =    .43001

------------------------------------------------------------------------------------------------
                        votinc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
-------------------------------+----------------------------------------------------------------
                     randtreat |
                         post  |   .0183537   .0116489     1.58   0.115    -.0044811    .0411886
                   1.regattack |    .020486   .0225344     0.91   0.363    -.0236872    .0646592
                               |
           randtreat#regattack |
                       post#1  |  -.0590377   .0335276    -1.76   0.078    -.1247604    .0066851
                               |
                        female |  -.0271195   .0108677    -2.50   0.013    -.0484229    -.005816
                           age |   .0007691   .0017285     0.44   0.656    -.0026191    .0041573
                               |
                   c.age#c.age |    .000015   .0000182     0.82   0.411    -.0000207    .0000507
                               |
                           edu |   .0165411   .0025428     6.51   0.000     .0115566    .0215255
                               |
                         emplo |
                   unemployed  |   .0043265   .0170157     0.25   0.799    -.0290288    .0376817
                      student  |   .0160735   .0208206     0.77   0.440    -.0247402    .0568872
                      retired  |   .0479379   .0194955     2.46   0.014     .0097216    .0861542
                    housework  |   .0454197   .0163868     2.77   0.006     .0132973    .0775421
                               |
                         munsz |
    2.001 a 10.000 habitantes  |  -.0755796   .0210113    -3.60   0.000    -.1167671   -.0343921
   10.001 a 50.000 habitantes  |  -.0749017   .0204097    -3.67   0.000      -.11491   -.0348935
  50.001 a 100.000 habitantes  |  -.0555103   .0235049    -2.36   0.018     -.101586   -.0094346
   100001 a 400000 habitantes  |  -.0356093   .0204833    -1.74   0.082    -.0757619    .0045433
400001 a 1.000.000 habitantes  |  -.0581855   .0262296    -2.22   0.027    -.1096023   -.0067688
  Más de 1.000.000 habitantes  |  -.0532341   .0263423    -2.02   0.043    -.1048718   -.0015963
                               |
                          ccaa |
                       Aragón  |   .0089762   .0276444     0.32   0.745     -.045214    .0631664
                     Asturias  |  -.0939441    .031113    -3.02   0.003    -.1549335   -.0329547
                     Baleares  |    .028025   .0392954     0.71   0.476    -.0490042    .1050541
                     Canarias  |   .0327666   .0275184     1.19   0.234    -.0211765    .0867097
                    Cantabria  |   .0232664   .0388427     0.60   0.549    -.0528753    .0994081
           Castilla-la Mancha  |    .040755    .027382     1.49   0.137    -.0129208    .0944308
                Castilla-León  |   .0635618   .0221147     2.87   0.004     .0202113    .1069122
                     Cataluña  |   -.137669   .0181216    -7.60   0.000     -.173192    -.102146
         Comunidad Valenciana  |   .1220954   .0197696     6.18   0.000     .0833419     .160849
                   E5remadura  |   .0991944   .0324446     3.06   0.002     .0355947     .162794
                      Galicia  |   .0296507   .0225441     1.32   0.188    -.0145415    .0738429
                       Madrid  |   .0363066   .0220937     1.64   0.100    -.0070027     .079616
                       Murcia  |   .1476813     .03333     4.43   0.000     .0823459    .2130168
                      Navarra  |  -.0608566   .0447483    -1.36   0.174    -.1485748    .0268615
                   País Vasco  |  -.2274875   .0233541    -9.74   0.000    -.2732675   -.1817074
                        Rioja  |   .0316345   .0591113     0.54   0.593    -.0842387    .1475077
                               |
                       studyid |
                         0499  |  -.0379547   .0196544    -1.93   0.054    -.0764823    .0005729
                         0799  |  -.0103318   .0158785    -0.65   0.515    -.0414577     .020794
                         1098  |  -.0149688   .0174239    -0.86   0.390    -.0491241    .0191865
                         1099  |  -.0148484   .0162331    -0.91   0.360    -.0466694    .0169725
                               |
                         _cons |    .198386   .0490756     4.04   0.000     .1021852    .2945867
------------------------------------------------------------------------------------------------

. estadd local controls "Yes"

added macro:
           e(controls) : "Yes"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "No"

added macro:
                e(imb) : "No"

. estadd local n = e(N)

added macro:
                  e(n) : "8159"

. 
. eststo basincconimb: reg votinc i.randtreat##i.regattack female c.age##c.age edu i.emplo##i.regattack i.m
> unsz##i.regattack i.ccaa i.studyid 

      Source |       SS           df       MS      Number of obs   =     8,159
-------------+----------------------------------   F(47, 8111)     =     11.82
       Model |  102.724229        47   2.1856219   Prob > F        =    0.0000
    Residual |  1499.44638     8,111  .184865785   R-squared       =    0.0641
-------------+----------------------------------   Adj R-squared   =    0.0587
       Total |  1602.17061     8,158  .196392573   Root MSE        =    .42996

--------------------------------------------------------------------------------------------------
                          votinc | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
---------------------------------+----------------------------------------------------------------
                       randtreat |
                           post  |   .0179771   .0116535     1.54   0.123    -.0048667    .0408208
                     1.regattack |  -.0111326   .0794594    -0.14   0.889    -.1668934    .1446281
                                 |
             randtreat#regattack |
                         post#1  |  -.0467619   .0356739    -1.31   0.190     -.116692    .0231681
                                 |
                          female |  -.0270886   .0108682    -2.49   0.013     -.048393   -.0057842
                             age |   .0007269   .0017291     0.42   0.674    -.0026625    .0041163
                                 |
                     c.age#c.age |   .0000157   .0000182     0.86   0.388      -.00002    .0000514
                                 |
                             edu |   .0166558   .0025468     6.54   0.000     .0116634    .0216482
                                 |
                           emplo |
                     unemployed  |   .0110403   .0180735     0.61   0.541    -.0243885    .0464691
                        student  |   .0085345   .0217219     0.39   0.694     -.034046     .051115
                        retired  |   .0517075    .019876     2.60   0.009     .0127455    .0906694
                      housework  |   .0518472   .0169287     3.06   0.002     .0186627    .0850317
                                 |
                 emplo#regattack |
                   unemployed#1  |  -.0597523   .0515738    -1.16   0.247    -.1608502    .0413456
                      student#1  |   .0700012   .0601676     1.16   0.245    -.0479426    .1879451
                      retired#1  |  -.0571418   .0476196    -1.20   0.230    -.1504884    .0362048
                    housework#1  |  -.0708221   .0455366    -1.56   0.120    -.1600854    .0184413
                                 |
                           munsz |
      2.001 a 10.000 habitantes  |   -.078383   .0217564    -3.60   0.000    -.1210312   -.0357348
     10.001 a 50.000 habitantes  |  -.0795336   .0210702    -3.77   0.000    -.1208366   -.0382305
    50.001 a 100.000 habitantes  |  -.0595275   .0242869    -2.45   0.014    -.1071362   -.0119189
     100001 a 400000 habitantes  |  -.0424131   .0211447    -2.01   0.045    -.0838622    -.000964
  400001 a 1.000.000 habitantes  |  -.0535225   .0273952    -1.95   0.051    -.1072241    .0001791
    Más de 1.000.000 habitantes  |  -.0485809   .0275909    -1.76   0.078    -.1026662    .0055044
                                 |
                 munsz#regattack |
    2.001 a 10.000 habitantes#1  |   .0444583   .0846334     0.53   0.599    -.1214449    .2103615
   10.001 a 50.000 habitantes#1  |   .0797431     .08317     0.96   0.338    -.0832914    .2427776
  50.001 a 100.000 habitantes#1  |   .0544134   .0941113     0.58   0.563     -.130069    .2388958
   100001 a 400000 habitantes#1  |   .0933262   .0828268     1.13   0.260    -.0690357     .255688
400001 a 1.000.000 habitantes#1  |  -.0069077   .0953231    -0.07   0.942    -.1937654      .17995
  Más de 1.000.000 habitantes#1  |   .0090966   .0841344     0.11   0.914    -.1558285    .1740216
                                 |
                            ccaa |
                         Aragón  |   .0037117   .0279885     0.13   0.895     -.051153    .0585763
                       Asturias  |  -.0935555   .0311799    -3.00   0.003    -.1546762   -.0324349
                       Baleares  |   .0294088   .0393229     0.75   0.455    -.0476742    .1064918
                       Canarias  |   .0345338   .0275819     1.25   0.211    -.0195339    .0886014
                      Cantabria  |   .0242635   .0388982     0.62   0.533     -.051987     .100514
             Castilla-la Mancha  |   .0400104   .0274798     1.46   0.145    -.0138572    .0938779
                  Castilla-León  |   .0632594   .0222222     2.85   0.004     .0196982    .1068207
                       Cataluña  |  -.1406474   .0181721    -7.74   0.000    -.1762693   -.1050254
           Comunidad Valenciana  |     .12084    .019944     6.06   0.000     .0817446    .1599354
                     E5remadura  |   .0978081   .0325418     3.01   0.003     .0340179    .1615983
                        Galicia  |   .0298761   .0226409     1.32   0.187    -.0145058     .074258
                         Madrid  |   .0354644   .0222316     1.60   0.111    -.0081152    .0790441
                         Murcia  |   .1491015   .0333782     4.47   0.000     .0836717    .2145314
                        Navarra  |  -.0625589   .0450532    -1.39   0.165    -.1508747    .0257569
                     País Vasco  |  -.2302095   .0234311    -9.82   0.000    -.2761404   -.1842786
                          Rioja  |   .0317967   .0591856     0.54   0.591    -.0842223    .1478156
                                 |
                         studyid |
                           0499  |  -.0381597   .0196676    -1.94   0.052    -.0767133    .0003938
                           0799  |  -.0076227   .0160738    -0.47   0.635    -.0391314     .023886
                           1098  |  -.0134898   .0175793    -0.77   0.443    -.0479498    .0209702
                           1099  |  -.0135075   .0162478    -0.83   0.406    -.0453573    .0183423
                                 |
                           _cons |   .1989326   .0493477     4.03   0.000     .1021984    .2956667
--------------------------------------------------------------------------------------------------

. estadd local controls "Yes"

added macro:
           e(controls) : "Yes"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "Yes"

added macro:
                e(imb) : "Yes"

. estadd local n = e(N)

added macro:
                  e(n) : "8159"

. 
. 
. 
. ** TABLE D6
. esttab bas bascon basint basinccon basincconimb ///
> , replace noomitted label nonotes noobs nodepvar nomtitles ///
> keep(1.randtreat 1.regattack 1.randtreat#1.regattack) ///
>  coeflabels(1.randtreat "Post" 1.regattack "Target region" 1.randtreat#1.regattack "Post X Target") ///
>  b(%9.2f) se(%9.2f) ///
>  scalars("controls Controls" "attack_fe False Attack FE" "region_fe Region FE" "imb Imbalance inter." "n 
> N. of observations") ///
>  starlevels(+ 0.1 * 0.05 ** 0.01 *** 0.001) ///
>  addnotes("Standard errors in parentheses" "+ p<.10, * p<.05, ** p<.01, *** p<.001.")

----------------------------------------------------------------------------------------------------
                              (1)             (2)             (3)             (4)             (5)   
----------------------------------------------------------------------------------------------------
Post                         0.01            0.01            0.01            0.02            0.02   
                           (0.01)          (0.01)          (0.01)          (0.01)          (0.01)   

Target region                                                0.02            0.02           -0.01   
                                                           (0.02)          (0.02)          (0.08)   

Post X Target                                               -0.05           -0.06+          -0.05   
                                                           (0.03)          (0.03)          (0.04)   
----------------------------------------------------------------------------------------------------
Controls                       No             Yes              No             Yes             Yes   
False Attack FE               Yes             Yes             Yes             Yes             Yes   
Region FE                     Yes             Yes             Yes             Yes             Yes   
Imbalance inter.               No              No              No              No             Yes   
N. of observations           9028            8159            9028            8159            8159   
----------------------------------------------------------------------------------------------------
Standard errors in parentheses
+ p<.10, * p<.05, ** p<.01, *** p<.001.

. 
. eststo clear 

. 
. 
. 
. /*******************************************************************************
>                          MODELS FOR X20 DATASET
> *******************************************************************************/
. 
. 
. use "harmonized dataset\allbar20", clear

. 
. 
. ** needed for the balance tests
. tabulate emplo, gen(em)

  RECODE of |
        P42 |      Freq.     Percent        Cum.
------------+-----------------------------------
   employed |    104,500       42.18       42.18
 unemployed |     24,160        9.75       51.94
    student |     19,160        7.73       59.67
    retired |     54,240       21.90       81.57
  housework |     45,660       18.43      100.00
------------+-----------------------------------
      Total |    247,720      100.00

. tabulate munsz, gen(mu)

            Tamaño de habitat |      Freq.     Percent        Cum.
------------------------------+-----------------------------------
     Menos de 2000 habitantes |     19,980        8.01        8.01
    2.001 a 10.000 habitantes |     40,320       16.17       24.18
   10.001 a 50.000 habitantes |     59,140       23.72       47.90
  50.001 a 100.000 habitantes |     23,940        9.60       57.50
   100001 a 400000 habitantes |     59,660       23.93       81.42
400001 a 1.000.000 habitantes |     16,480        6.61       88.03
  Más de 1.000.000 habitantes |     29,840       11.97      100.00
------------------------------+-----------------------------------
                        Total |    249,360      100.00

. 
. 
. ** balance tests
. reg female i.randtreat100##i.regattack100 i.studyid i.randdate100 
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,329
-------------+----------------------------------   F(18, 144310)   =      1.14
       Model |  5.10187869        18  .283437705   Prob > F        =    0.3090
    Residual |   36031.652   144,310  .249682295   R-squared       =    0.0001
-------------+----------------------------------   Adj R-squared   =    0.0000
       Total |  36036.7539   144,328  .249686505   Root MSE        =    .49968

-------------------------------------------------------------------------------------------
                   female | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |  -.0023606   .0036115    -0.65   0.513    -.0094391    .0047179
           1.regattack100 |   .0137839   .0074796     1.84   0.065     -.000876    .0284438
                          |
randtreat100#regattack100 |
                  post#1  |  -.0038423   .0098814    -0.39   0.697    -.0232095     .015525
                          |
                  studyid |
                    0499  |   .0137247   .0106894     1.28   0.199    -.0072263    .0346757
                    0799  |    .003037   .0101191     0.30   0.764    -.0167962    .0228701
                    1098  |   .0051044   .0094296     0.54   0.588    -.0133776    .0235863
                    1099  |   .0013011   .0098651     0.13   0.895    -.0180343    .0206365
                          |
              randdate100 |
                   14181  |  -.0018089   .0068617    -0.26   0.792    -.0152577      .01164
                   14182  |  -.0047305   .0091369    -0.52   0.605    -.0226387    .0131776
                   14272  |  -.0024629   .0093322    -0.26   0.792    -.0207538    .0158281
                   14273  |  -.0076779   .0115452    -0.67   0.506    -.0303063    .0149505
                   14274  |          0  (omitted)
                   14359  |     -.0056   .0086932    -0.64   0.519    -.0226385    .0114386
                   14360  |  -.0260685   .0107035    -2.44   0.015     -.047047   -.0050899
                   14361  |          0  (omitted)
                   14435  |  -.0022475   .0079145    -0.28   0.776    -.0177599    .0132648
                   14436  |   .0020844   .0081263     0.26   0.798    -.0138429    .0180117
                   14438  |   .0017749   .0081945     0.22   0.829    -.0142861    .0178359
                   14439  |          0  (omitted)
                   14540  |   .0009524   .0090111     0.11   0.916    -.0167091     .018614
                   14541  |   .0011302    .006749     0.17   0.867    -.0120977    .0143582
                   14542  |          0  (omitted)
                          |
                    _cons |   .5158879   .0082644    62.42   0.000     .4996898     .532086
-------------------------------------------------------------------------------------------

. 
. reg age i.randtreat100##i.regattack100 i.studyid  i.randdate100 
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,238
-------------+----------------------------------   F(18, 144219)   =      1.73
       Model |  10476.8831        18  582.049063   Prob > F        =    0.0281
    Residual |  48590203.3   144,219  336.919569   R-squared       =    0.0002
-------------+----------------------------------   Adj R-squared   =    0.0001
       Total |  48600680.2   144,237   336.95016   Root MSE        =    18.355

-------------------------------------------------------------------------------------------
                      age | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |   -.204053   .1326911    -1.54   0.124    -.4641249    .0560188
           1.regattack100 |  -.1122184   .2748663    -0.41   0.683     -.650951    .4265142
                          |
randtreat100#regattack100 |
                  post#1  |  -.4380623   .3631955    -1.21   0.228    -1.149918    .2737938
                          |
                  studyid |
                    0499  |   .1996059   .3927584     0.51   0.611     -.570193    .9694048
                    0799  |    .173055   .3718133     0.47   0.642    -.5556918    .9018018
                    1098  |   .7150439   .3465072     2.06   0.039     .0358966    1.394191
                    1099  |    .142917   .3625183     0.39   0.693    -.5676119    .8534459
                          |
              randdate100 |
                   14181  |  -.5056479   .2521473    -2.01   0.045    -.9998516   -.0114441
                   14182  |  -.5459606   .3357686    -1.63   0.104     -1.20406    .1121393
                   14272  |   .3081293   .3429401     0.90   0.369    -.3640265    .9802852
                   14273  |   .1045646   .4244136     0.25   0.805    -.7272777     .936407
                   14274  |          0  (omitted)
                   14359  |  -.0028168   .3193909    -0.01   0.993    -.6288166    .6231831
                   14360  |   .1255939   .3933979     0.32   0.750    -.6454582     .896646
                   14361  |          0  (omitted)
                   14435  |   .4709212   .2907403     1.62   0.105    -.0989241    1.040766
                   14436  |   .0549404   .2985144     0.18   0.854     -.530142    .6400228
                   14438  |   .1201317   .3010164     0.40   0.690    -.4698546     .710118
                   14439  |          0  (omitted)
                   14540  |  -.4868066   .3310499    -1.47   0.141    -1.135658    .1620447
                   14541  |  -.1249354     .24799    -0.50   0.614    -.6109909    .3611202
                   14542  |          0  (omitted)
                          |
                    _cons |   45.12716   .3037039   148.59   0.000     44.53191    45.72242
-------------------------------------------------------------------------------------------

. 
. reg edu i.randtreat100##i.regattack100 i.studyid  i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   131,162
-------------+----------------------------------   F(18, 131143)   =     28.61
       Model |  2540.11177        18  141.117321   Prob > F        =    0.0000
    Residual |  646885.842   131,143  4.93267534   R-squared       =    0.0039
-------------+----------------------------------   Adj R-squared   =    0.0038
       Total |  649425.954   131,161  4.95136476   Root MSE        =     2.221

-------------------------------------------------------------------------------------------
                      edu | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |  -.0795815   .0168294    -4.73   0.000    -.1125669   -.0465961
           1.regattack100 |   .3637617   .0347396    10.47   0.000     .2956726    .4318507
                          |
randtreat100#regattack100 |
                  post#1  |   .1823872   .0455236     4.01   0.000     .0931618    .2716125
                          |
                  studyid |
                    0499  |   .0275896   .0497701     0.55   0.579     -.069959    .1251382
                    0799  |   .0321464   .0470036     0.68   0.494    -.0599798    .1242726
                    1098  |    .035395   .0438234     0.81   0.419    -.0504981    .1212882
                    1099  |  -.0191945   .0458405    -0.42   0.675    -.1090411    .0706521
                          |
              randdate100 |
                   14181  |  -.0688206   .0320923    -2.14   0.032    -.1317209   -.0059203
                   14182  |  -.0319269   .0427457    -0.75   0.455    -.1157078    .0518539
                   14272  |    .048635   .0433282     1.12   0.262    -.0362874    .1335575
                   14273  |   .1441722   .0536724     2.69   0.007     .0389753    .2493691
                   14274  |          0  (omitted)
                   14359  |   .1201672   .0406551     2.96   0.003      .040484    .1998504
                   14360  |    .038342   .0502145     0.76   0.445    -.0600774    .1367614
                   14361  |          0  (omitted)
                   14435  |   .0466878   .0369006     1.27   0.206    -.0256367    .1190124
                   14436  |   .0535443   .0378502     1.41   0.157    -.0206415      .12773
                   14438  |  -.0266476   .0382501    -0.70   0.486    -.1016171    .0483218
                   14439  |          0  (omitted)
                   14540  |   .0401423   .0419474     0.96   0.339    -.0420737    .1223584
                   14541  |   .0520398   .0314434     1.66   0.098    -.0095888    .1136684
                   14542  |          0  (omitted)
                          |
                    _cons |   3.909018   .0383123   102.03   0.000     3.833927     3.98411
-------------------------------------------------------------------------------------------

. 
. reg em1 i.randtreat100##i.regattack100 i.studyid  i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   143,330
-------------+----------------------------------   F(18, 143311)   =     24.71
       Model |  108.333986        18   6.0185548   Prob > F        =    0.0000
    Residual |  34911.4342   143,311  .243606103   R-squared       =    0.0031
-------------+----------------------------------   Adj R-squared   =    0.0030
       Total |  35019.7682   143,329  .244331351   Root MSE        =    .49356

-------------------------------------------------------------------------------------------
                      em1 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |  -.0132752   .0035807    -3.71   0.000    -.0202934   -.0062571
           1.regattack100 |   .0171293   .0074196     2.31   0.021      .002587    .0316716
                          |
randtreat100#regattack100 |
                  post#1  |   .0260751   .0097934     2.66   0.008     .0068802      .04527
                          |
                  studyid |
                    0499  |   .0284023   .0105829     2.68   0.007     .0076601    .0491446
                    0799  |   .0258037   .0100262     2.57   0.010     .0061526    .0454548
                    1098  |  -.0251413   .0093427    -2.69   0.007    -.0434528   -.0068298
                    1099  |    .046083   .0097745     4.71   0.000     .0269252    .0652409
                          |
              randdate100 |
                   14181  |  -.0020788    .006803    -0.31   0.760    -.0154124    .0112549
                   14182  |  -.0022265   .0090569    -0.25   0.806    -.0199779    .0155249
                   14272  |   .0270679    .009245     2.93   0.003      .008948    .0451879
                   14273  |   .0414854   .0114411     3.63   0.000     .0190611    .0639097
                   14274  |          0  (omitted)
                   14359  |   .0097486   .0086031     1.13   0.257    -.0071133    .0266104
                   14360  |   .0228171   .0106009     2.15   0.031     .0020395    .0435948
                   14361  |          0  (omitted)
                   14435  |   .0091732   .0078482     1.17   0.242    -.0062091    .0245555
                   14436  |   .0093833   .0080567     1.16   0.244    -.0064076    .0251743
                   14438  |  -.0028658   .0081223    -0.35   0.724    -.0187853    .0130537
                   14439  |          0  (omitted)
                   14540  |  -.0101541   .0089398    -1.14   0.256    -.0276759    .0073676
                   14541  |  -.0073619   .0066904    -1.10   0.271     -.020475    .0057513
                   14542  |          0  (omitted)
                          |
                    _cons |   .4081124   .0081868    49.85   0.000     .3920663    .4241584
-------------------------------------------------------------------------------------------

. reg em2 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   143,330
-------------+----------------------------------   F(18, 143311)   =     20.10
       Model |  31.9435922        18  1.77464401   Prob > F        =    0.0000
    Residual |   12653.659   143,311    .0882951   R-squared       =    0.0025
-------------+----------------------------------   Adj R-squared   =    0.0024
       Total |  12685.6026   143,329   .08850688   Root MSE        =    .29714

-------------------------------------------------------------------------------------------
                      em2 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |   .0114102   .0021557     5.29   0.000     .0071851    .0156354
           1.regattack100 |   .0065122   .0044669     1.46   0.145    -.0022428    .0152672
                          |
randtreat100#regattack100 |
                  post#1  |  -.0206961    .005896    -3.51   0.000    -.0322522     -.00914
                          |
                  studyid |
                    0499  |   .0026465   .0063713     0.42   0.678    -.0098411    .0151342
                    0799  |    .003216   .0060361     0.53   0.594    -.0086147    .0150468
                    1098  |   .0311924   .0056247     5.55   0.000     .0201682    .0422166
                    1099  |  -.0097134   .0058846    -1.65   0.099    -.0212472    .0018203
                          |
              randdate100 |
                   14181  |   .0004798   .0040956     0.12   0.907    -.0075476    .0085072
                   14182  |   .0038237   .0054526     0.70   0.483    -.0068633    .0145108
                   14272  |  -.0011195   .0055658    -0.20   0.841    -.0120285    .0097894
                   14273  |  -.0086377    .006888    -1.25   0.210     -.022138    .0048625
                   14274  |          0  (omitted)
                   14359  |  -.0033933   .0051794    -0.66   0.512    -.0135447    .0067582
                   14360  |  -.0058612   .0063822    -0.92   0.358    -.0183701    .0066478
                   14361  |          0  (omitted)
                   14435  |  -.0098297   .0047249    -2.08   0.037    -.0190904    -.000569
                   14436  |  -.0072197   .0048504    -1.49   0.137    -.0167264    .0022871
                   14438  |   .0025528   .0048899     0.52   0.602    -.0070313     .012137
                   14439  |          0  (omitted)
                   14540  |   .0118455   .0053821     2.20   0.028     .0012968    .0223943
                   14541  |   .0077874   .0040279     1.93   0.053    -.0001072     .015682
                   14542  |          0  (omitted)
                          |
                    _cons |   .0873807   .0049288    17.73   0.000     .0777204    .0970411
-------------------------------------------------------------------------------------------

. reg em3 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   143,330
-------------+----------------------------------   F(18, 143311)   =      3.69
       Model |  4.57699273        18  .254277374   Prob > F        =    0.0000
    Residual |  9864.30053   143,311  .068831426   R-squared       =    0.0005
-------------+----------------------------------   Adj R-squared   =    0.0003
       Total |  9868.87753   143,329  .068854716   Root MSE        =    .26236

-------------------------------------------------------------------------------------------
                      em3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |  -.0086348   .0019033    -4.54   0.000    -.0123653   -.0049043
           1.regattack100 |   -.003163   .0039439    -0.80   0.423     -.010893    .0045671
                          |
randtreat100#regattack100 |
                  post#1  |   .0175709   .0052058     3.38   0.001     .0073677    .0277741
                          |
                  studyid |
                    0499  |  -.0027819   .0056254    -0.49   0.621    -.0138076    .0082438
                    0799  |  -.0108396   .0053295    -2.03   0.042    -.0212853   -.0003939
                    1098  |  -.0104146   .0049662    -2.10   0.036    -.0201482    -.000681
                    1099  |  -.0154731   .0051957    -2.98   0.003    -.0256566   -.0052896
                          |
              randdate100 |
                   14181  |  -.0004316   .0036162    -0.12   0.905    -.0075192     .006656
                   14182  |   .0011213   .0048143     0.23   0.816    -.0083146    .0105572
                   14272  |  -.0030025   .0049142    -0.61   0.541    -.0126343    .0066292
                   14273  |  -.0000943   .0060816    -0.02   0.988     -.012014    .0118255
                   14274  |          0  (omitted)
                   14359  |   .0028976    .004573     0.63   0.526    -.0060654    .0118606
                   14360  |  -.0032058    .005635    -0.57   0.569    -.0142503    .0078386
                   14361  |          0  (omitted)
                   14435  |   .0067854   .0041718     1.63   0.104    -.0013912    .0149619
                   14436  |   .0065801   .0042826     1.54   0.124    -.0018137    .0149739
                   14438  |   .0033531   .0043174     0.78   0.437     -.005109    .0118152
                   14439  |          0  (omitted)
                   14540  |   .0077688    .004752     1.63   0.102     -.001545    .0170826
                   14541  |   .0052285   .0035563     1.47   0.142    -.0017418    .0121989
                   14542  |          0  (omitted)
                          |
                    _cons |   .0852938   .0043518    19.60   0.000     .0767644    .0938232
-------------------------------------------------------------------------------------------

. reg em4 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   143,330
-------------+----------------------------------   F(18, 143311)   =      3.25
       Model |  9.99167604        18  .555093113   Prob > F        =    0.0000
    Residual |  24487.4476   143,311  .170869282   R-squared       =    0.0004
-------------+----------------------------------   Adj R-squared   =    0.0003
       Total |  24497.4393   143,329  .170917535   Root MSE        =    .41336

-------------------------------------------------------------------------------------------
                      em4 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |   .0126092   .0029989     4.20   0.000     .0067314    .0184869
           1.regattack100 |  -.0061907    .006214    -1.00   0.319    -.0183699    .0059886
                          |
randtreat100#regattack100 |
                  post#1  |  -.0153216   .0082021    -1.87   0.062    -.0313975    .0007543
                          |
                  studyid |
                    0499  |   .0041665   .0088632     0.47   0.638    -.0132053    .0215382
                    0799  |   .0054138    .008397     0.64   0.519    -.0110441    .0218717
                    1098  |   .0108845   .0078246     1.39   0.164    -.0044515    .0262205
                    1099  |   .0060249   .0081862     0.74   0.462    -.0100198    .0220697
                          |
              randdate100 |
                   14181  |  -.0005348   .0056975    -0.09   0.925    -.0117018    .0106323
                   14182  |  -.0029147   .0075852    -0.38   0.701    -.0177816    .0119522
                   14272  |   -.008872   .0077427    -1.15   0.252    -.0240475    .0063036
                   14273  |  -.0153286    .009582    -1.60   0.110     -.034109    .0034519
                   14274  |          0  (omitted)
                   14359  |  -.0035362   .0072051    -0.49   0.624    -.0176581    .0105857
                   14360  |   .0047623   .0088783     0.54   0.592    -.0126391    .0221636
                   14361  |          0  (omitted)
                   14435  |   -.003424   .0065729    -0.52   0.602    -.0163067    .0094588
                   14436  |   -.007168   .0067475    -1.06   0.288     -.020393     .006057
                   14438  |   .0002826   .0068025     0.04   0.967    -.0130501    .0136152
                   14439  |          0  (omitted)
                   14540  |  -.0068792   .0074871    -0.92   0.358    -.0215538    .0077953
                   14541  |  -.0034619   .0056033    -0.62   0.537    -.0144442    .0075204
                   14542  |          0  (omitted)
                          |
                    _cons |   .2109757   .0068565    30.77   0.000     .1975371    .2244144
-------------------------------------------------------------------------------------------

. reg em5 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   143,330
-------------+----------------------------------   F(18, 143311)   =      8.79
       Model |  23.7209626        18  1.31783126   Prob > F        =    0.0000
    Residual |  21495.9635   143,311   .14999521   R-squared       =    0.0011
-------------+----------------------------------   Adj R-squared   =    0.0010
       Total |  21519.6845   143,329  .150141873   Root MSE        =    .38729

-------------------------------------------------------------------------------------------
                      em5 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |  -.0021093   .0028097    -0.75   0.453    -.0076163    .0033977
           1.regattack100 |  -.0142879   .0058221    -2.45   0.014     -.025699   -.0028767
                          |
randtreat100#regattack100 |
                  post#1  |  -.0076283   .0076847    -0.99   0.321    -.0226902    .0074337
                          |
                  studyid |
                    0499  |  -.0324334   .0083042    -3.91   0.000    -.0487095   -.0161573
                    0799  |  -.0235939   .0078674    -3.00   0.003    -.0390138    -.008174
                    1098  |   -.006521   .0073311    -0.89   0.374    -.0208897    .0078477
                    1099  |  -.0269215   .0076699    -3.51   0.000    -.0419543   -.0118887
                          |
              randdate100 |
                   14181  |   .0025653   .0053382     0.48   0.631    -.0078974     .013028
                   14182  |   .0001961   .0071068     0.03   0.978    -.0137331    .0141253
                   14272  |  -.0140739   .0072544    -1.94   0.052    -.0282923    .0001446
                   14273  |  -.0174248   .0089776    -1.94   0.052    -.0350208    .0001711
                   14274  |          0  (omitted)
                   14359  |  -.0057167   .0067507    -0.85   0.397    -.0189479    .0075145
                   14360  |  -.0185124   .0083184    -2.23   0.026    -.0348163   -.0022086
                   14361  |          0  (omitted)
                   14435  |  -.0027049   .0061583    -0.44   0.660    -.0147751    .0093653
                   14436  |  -.0015758    .006322    -0.25   0.803    -.0139667    .0108151
                   14438  |  -.0033228   .0063734    -0.52   0.602    -.0158145     .009169
                   14439  |          0  (omitted)
                   14540  |   -.002581   .0070149    -0.37   0.713      -.01633    .0111681
                   14541  |  -.0021922   .0052499    -0.42   0.676    -.0124818    .0080975
                   14542  |          0  (omitted)
                          |
                    _cons |   .2082374   .0064241    32.42   0.000     .1956463    .2208284
-------------------------------------------------------------------------------------------

. 
. reg mu1 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,344
-------------+----------------------------------   F(18, 144325)   =     24.69
       Model |  34.6643822        18  1.92579901   Prob > F        =    0.0000
    Residual |  11258.6758   144,325  .078009186   R-squared       =    0.0031
-------------+----------------------------------   Adj R-squared   =    0.0029
       Total |  11293.3402   144,343  .078239611   Root MSE        =     .2793

-------------------------------------------------------------------------------------------
                      mu1 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |  -.0197518   .0020185    -9.79   0.000     -.023708   -.0157957
           1.regattack100 |  -.0399992   .0041804    -9.57   0.000    -.0481926   -.0318058
                          |
randtreat100#regattack100 |
                  post#1  |   .0043794   .0055229     0.79   0.428    -.0064454    .0152042
                          |
                  studyid |
                    0499  |  -.0013538    .005974    -0.23   0.821    -.0130628    .0103551
                    0799  |  -.0093352   .0056561    -1.65   0.099    -.0204211    .0017507
                    1098  |    .007459   .0052707     1.42   0.157    -.0028715    .0177895
                    1099  |   .0157496   .0055142     2.86   0.004      .004942    .0265573
                          |
              randdate100 |
                   14181  |   .0063661   .0038354     1.66   0.097    -.0011512    .0138833
                   14182  |   -.025746   .0051071    -5.04   0.000    -.0357558   -.0157362
                   14272  |    .019928   .0052163     3.82   0.000     .0097043    .0301518
                   14273  |   .0107164   .0064533     1.66   0.097    -.0019319    .0233646
                   14274  |          0  (omitted)
                   14359  |   .0072925   .0048572     1.50   0.133    -.0022276    .0168126
                   14360  |   .0171741   .0059799     2.87   0.004     .0054536    .0288947
                   14361  |          0  (omitted)
                   14435  |   .0166322   .0044238     3.76   0.000     .0079616    .0253028
                   14436  |   .0047224   .0045422     1.04   0.298    -.0041802    .0136251
                   14438  |    .003831   .0045804     0.84   0.403    -.0051464    .0128085
                   14439  |          0  (omitted)
                   14540  |  -.0299348   .0050368    -5.94   0.000    -.0398068   -.0200628
                   14541  |  -.0197559   .0037724    -5.24   0.000    -.0271498   -.0123621
                   14542  |          0  (omitted)
                          |
                    _cons |    .094805   .0046194    20.52   0.000      .085751     .103859
-------------------------------------------------------------------------------------------

. reg mu2 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,344
-------------+----------------------------------   F(18, 144325)   =     54.36
       Model |  137.768995        18  7.65383305   Prob > F        =    0.0000
    Residual |  20321.1177   144,325  .140801093   R-squared       =    0.0067
-------------+----------------------------------   Adj R-squared   =    0.0066
       Total |  20458.8867   144,343   .14173799   Root MSE        =    .37523

-------------------------------------------------------------------------------------------
                      mu2 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |  -.0223355   .0027118    -8.24   0.000    -.0276505   -.0170205
           1.regattack100 |  -.0778469   .0056162   -13.86   0.000    -.0888545   -.0668392
                          |
randtreat100#regattack100 |
                  post#1  |   .0155978   .0074199     2.10   0.036     .0010549    .0301407
                          |
                  studyid |
                    0499  |   .0195315   .0080259     2.43   0.015     .0038009    .0352622
                    0799  |   .0165625   .0075989     2.18   0.029     .0016689    .0314562
                    1098  |   .0504098   .0070811     7.12   0.000      .036531    .0642886
                    1099  |   .0609394   .0074082     8.23   0.000     .0464196    .0754593
                          |
              randdate100 |
                   14181  |   -.015265   .0051527    -2.96   0.003    -.0253643   -.0051658
                   14182  |  -.0131798   .0068613    -1.92   0.055    -.0266278    .0002681
                   14272  |   .0741657   .0070079    10.58   0.000     .0604303    .0879011
                   14273  |   .1070304   .0086698    12.35   0.000     .0900378    .1240231
                   14274  |          0  (omitted)
                   14359  |  -.0180493   .0065256    -2.77   0.006    -.0308394   -.0052593
                   14360  |   .0635953   .0080339     7.92   0.000      .047849    .0793416
                   14361  |          0  (omitted)
                   14435  |   .0301972   .0059433     5.08   0.000     .0185484     .041846
                   14436  |   .0006628   .0061023     0.11   0.914    -.0112977    .0126232
                   14438  |    .020224   .0061536     3.29   0.001     .0081631     .032285
                   14439  |          0  (omitted)
                   14540  |  -.0418054   .0067668    -6.18   0.000    -.0550682   -.0285426
                   14541  |  -.0175895   .0050681    -3.47   0.001     -.027523   -.0076561
                   14542  |          0  (omitted)
                          |
                    _cons |   .1462629   .0062061    23.57   0.000      .134099    .1584268
-------------------------------------------------------------------------------------------

. reg mu3 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,344
-------------+----------------------------------   F(18, 144325)   =     28.75
       Model |  94.5353655        18  5.25196475   Prob > F        =    0.0000
    Residual |  26362.0549   144,325  .182657577   R-squared       =    0.0036
-------------+----------------------------------   Adj R-squared   =    0.0034
       Total |  26456.5902   144,343  .183289735   Root MSE        =    .42738

-------------------------------------------------------------------------------------------
                      mu3 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |  -.0515668   .0030886   -16.70   0.000    -.0576205   -.0455131
           1.regattack100 |   -.033886   .0063967    -5.30   0.000    -.0464235   -.0213485
                          |
randtreat100#regattack100 |
                  post#1  |  -.0037089   .0084511    -0.44   0.661     -.020273    .0128551
                          |
                  studyid |
                    0499  |   .0094746   .0091414     1.04   0.300    -.0084423    .0273915
                    0799  |  -.0036154    .008655    -0.42   0.676     -.020579    .0133481
                    1098  |   .0587791   .0080652     7.29   0.000     .0429714    .0745868
                    1099  |   .0299009   .0084377     3.54   0.000     .0133631    .0464387
                          |
              randdate100 |
                   14181  |  -.0677438   .0058688   -11.54   0.000    -.0792467    -.056241
                   14182  |   -.065751   .0078148    -8.41   0.000    -.0810679   -.0504341
                   14272  |   .0587749   .0079819     7.36   0.000     .0431306    .0744192
                   14273  |   .0132768   .0098747     1.34   0.179    -.0060774    .0326311
                   14274  |          0  (omitted)
                   14359  |   .0261831   .0074325     3.52   0.000     .0116155    .0407507
                   14360  |   .0363868   .0091504     3.98   0.000     .0184521    .0543215
                   14361  |          0  (omitted)
                   14435  |   .0363434   .0067693     5.37   0.000     .0230756    .0496111
                   14436  |   .0354723   .0069504     5.10   0.000     .0218496     .049095
                   14438  |  -.0215341   .0070088    -3.07   0.002    -.0352713    -.007797
                   14439  |          0  (omitted)
                   14540  |   .0007481   .0077072     0.10   0.923     -.014358    .0158541
                   14541  |  -.0009796   .0057725    -0.17   0.865    -.0122936    .0103345
                   14542  |          0  (omitted)
                          |
                    _cons |   .2449989   .0070686    34.66   0.000     .2311445    .2588533
-------------------------------------------------------------------------------------------

. reg mu4 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,344
-------------+----------------------------------   F(18, 144325)   =     18.46
       Model |  28.6237693        18   1.5902094   Prob > F        =    0.0000
    Residual |  12435.8494   144,325  .086165595   R-squared       =    0.0023
-------------+----------------------------------   Adj R-squared   =    0.0022
       Total |  12464.4732   144,343  .086353153   Root MSE        =    .29354

-------------------------------------------------------------------------------------------
                      mu4 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |   .0183631   .0021214     8.66   0.000     .0142053    .0225209
           1.regattack100 |   .0221454   .0043935     5.04   0.000     .0135343    .0307565
                          |
randtreat100#regattack100 |
                  post#1  |  -.0529586   .0058045    -9.12   0.000    -.0643353   -.0415819
                          |
                  studyid |
                    0499  |   .0069994   .0062786     1.11   0.265    -.0053065    .0193052
                    0799  |    .000776   .0059445     0.13   0.896    -.0108751    .0124271
                    1098  |   .0084125   .0055394     1.52   0.129    -.0024447    .0192696
                    1099  |  -.0167709   .0057953    -2.89   0.004    -.0281296   -.0054123
                          |
              randdate100 |
                   14181  |  -.0217526   .0040309    -5.40   0.000     -.029653   -.0138521
                   14182  |  -.0142524   .0053674    -2.66   0.008    -.0247725   -.0037323
                   14272  |  -.0232655   .0054822    -4.24   0.000    -.0340105   -.0125206
                   14273  |  -.0262047   .0067822    -3.86   0.000    -.0394978   -.0129117
                   14274  |          0  (omitted)
                   14359  |  -.0106644   .0051049    -2.09   0.037    -.0206699    -.000659
                   14360  |  -.0187218   .0062848    -2.98   0.003    -.0310399   -.0064038
                   14361  |          0  (omitted)
                   14435  |  -.0100885   .0046494    -2.17   0.030    -.0192012   -.0009759
                   14436  |  -.0100082   .0047738    -2.10   0.036    -.0193647   -.0006518
                   14438  |   .0080901   .0048139     1.68   0.093    -.0013449    .0175252
                   14439  |          0  (omitted)
                   14540  |   .0331422   .0052936     6.26   0.000      .022767    .0435175
                   14541  |   .0116995   .0039647     2.95   0.003     .0039287    .0194703
                   14542  |          0  (omitted)
                          |
                    _cons |   .0923667   .0048549    19.03   0.000     .0828511    .1018823
-------------------------------------------------------------------------------------------

. reg mu5 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,344
-------------+----------------------------------   F(18, 144325)   =     35.34
       Model |  113.579171        18  6.30995394   Prob > F        =    0.0000
    Residual |  25772.2487   144,325  .178570925   R-squared       =    0.0044
-------------+----------------------------------   Adj R-squared   =    0.0043
       Total |  25885.8279   144,343  .179335527   Root MSE        =    .42258

-------------------------------------------------------------------------------------------
                      mu5 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |   .0189919   .0030539     6.22   0.000     .0130064    .0249775
           1.regattack100 |   .0012086   .0063248     0.19   0.848    -.0111878    .0136051
                          |
randtreat100#regattack100 |
                  post#1  |   .0972081   .0083561    11.63   0.000     .0808303    .1135858
                          |
                  studyid |
                    0499  |   .0118417   .0090385     1.31   0.190    -.0058736    .0295571
                    0799  |   .0163038   .0085576     1.91   0.057    -.0004689    .0330765
                    1098  |   -.034404   .0079745    -4.31   0.000    -.0500338   -.0187741
                    1099  |  -.0100048   .0083428    -1.20   0.230    -.0263565     .006347
                          |
              randdate100 |
                   14181  |   .0394482   .0058028     6.80   0.000     .0280748    .0508216
                   14182  |   .0407698   .0077269     5.28   0.000     .0256252    .0559144
                   14272  |  -.0302747   .0078921    -3.84   0.000     -.045743   -.0148064
                   14273  |  -.0321543   .0097636    -3.29   0.001    -.0512909   -.0130178
                   14274  |          0  (omitted)
                   14359  |    -.01441   .0073489    -1.96   0.050    -.0288137   -6.23e-06
                   14360  |  -.0950938   .0090475   -10.51   0.000    -.1128268   -.0773609
                   14361  |          0  (omitted)
                   14435  |  -.0431171   .0066932    -6.44   0.000    -.0562356   -.0299987
                   14436  |  -.0146665   .0068722    -2.13   0.033     -.028136    -.001197
                   14438  |  -.0050313     .00693    -0.73   0.468     -.018614    .0085513
                   14439  |          0  (omitted)
                   14540  |   .0211642   .0076205     2.78   0.005     .0062281    .0361003
                   14541  |   .0094199   .0057076     1.65   0.099    -.0017668    .0206066
                   14542  |          0  (omitted)
                          |
                    _cons |    .230429   .0069891    32.97   0.000     .2167305    .2441275
-------------------------------------------------------------------------------------------

. reg mu6 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,344
-------------+----------------------------------   F(18, 144325)   =     53.77
       Model |  59.9072359        18  3.32817977   Prob > F        =    0.0000
    Residual |  8933.68695   144,325  .061899788   R-squared       =    0.0067
-------------+----------------------------------   Adj R-squared   =    0.0065
       Total |  8993.59418   144,343  .062307103   Root MSE        =     .2488

-------------------------------------------------------------------------------------------
                      mu6 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |   .0237216    .001798    13.19   0.000     .0201976    .0272457
           1.regattack100 |  -.0463083   .0037238   -12.44   0.000    -.0536069   -.0390098
                          |
randtreat100#regattack100 |
                  post#1  |  -.0169989   .0049197    -3.46   0.001    -.0266415   -.0073564
                          |
                  studyid |
                    0499  |  -.0227192   .0053215    -4.27   0.000    -.0331493   -.0122891
                    0799  |  -.0302085   .0050384    -6.00   0.000    -.0400837   -.0203334
                    1098  |  -.0706507   .0046951   -15.05   0.000    -.0798529   -.0614484
                    1099  |  -.0494885   .0049119   -10.08   0.000    -.0591158   -.0398612
                          |
              randdate100 |
                   14181  |   .0434957   .0034165    12.73   0.000     .0367995    .0501919
                   14182  |   .0453187   .0045493     9.96   0.000     .0364021    .0542352
                   14272  |  -.0544389   .0046465   -11.72   0.000     -.063546   -.0453317
                   14273  |  -.0428645   .0057485    -7.46   0.000    -.0541313   -.0315976
                   14274  |          0  (omitted)
                   14359  |  -.0106413   .0043268    -2.46   0.014    -.0191217    -.002161
                   14360  |  -.0288763   .0053268    -5.42   0.000    -.0393168   -.0184359
                   14361  |          0  (omitted)
                   14435  |  -.0148707   .0039407    -3.77   0.000    -.0225944   -.0071471
                   14436  |  -.0086692   .0040461    -2.14   0.032    -.0165995   -.0007389
                   14438  |   .0028456   .0040801     0.70   0.486    -.0051513    .0108425
                   14439  |          0  (omitted)
                   14540  |   .0112547   .0044867     2.51   0.012     .0024609    .0200485
                   14541  |    .008509   .0033604     2.53   0.011     .0019226    .0150953
                   14542  |          0  (omitted)
                          |
                    _cons |    .100129   .0041149    24.33   0.000     .0920638    .1081941
-------------------------------------------------------------------------------------------

. reg mu7 i.randtreat100##i.regattack100 i.studyid i.randdate100  
note: 14274.randdate100 omitted because of collinearity.
note: 14361.randdate100 omitted because of collinearity.
note: 14439.randdate100 omitted because of collinearity.
note: 14542.randdate100 omitted because of collinearity.

      Source |       SS           df       MS      Number of obs   =   144,344
-------------+----------------------------------   F(18, 144325)   =    174.61
       Model |  289.982686        18  16.1101492   Prob > F        =    0.0000
    Residual |  13315.7113   144,325  .092261987   R-squared       =    0.0213
-------------+----------------------------------   Adj R-squared   =    0.0212
       Total |   13605.694   144,343  .094259465   Root MSE        =    .30375

-------------------------------------------------------------------------------------------
                      mu7 | Coefficient  Std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |   .0325775   .0021951    14.84   0.000     .0282751    .0368799
           1.regattack100 |   .1746863   .0045462    38.42   0.000     .1657758    .1835969
                          |
randtreat100#regattack100 |
                  post#1  |  -.0435188   .0060063    -7.25   0.000    -.0552911   -.0317466
                          |
                  studyid |
                    0499  |  -.0237742   .0064969    -3.66   0.000    -.0365079   -.0110405
                    0799  |   .0095168   .0061512     1.55   0.122    -.0025393     .021573
                    1098  |  -.0200057    .005732    -3.49   0.000    -.0312404    -.008771
                    1099  |  -.0303257   .0059968    -5.06   0.000    -.0420793   -.0185721
                          |
              randdate100 |
                   14181  |   .0154514    .004171     3.70   0.000     .0072763    .0236266
                   14182  |   .0328408   .0055541     5.91   0.000     .0219549    .0437266
                   14272  |  -.0448895   .0056728    -7.91   0.000    -.0560081   -.0337709
                   14273  |  -.0298001   .0070181    -4.25   0.000    -.0435554   -.0160448
                   14274  |          0  (omitted)
                   14359  |   .0202895   .0052824     3.84   0.000     .0099361    .0306428
                   14360  |   .0255358   .0065033     3.93   0.000     .0127894    .0382821
                   14361  |          0  (omitted)
                   14435  |  -.0150964    .004811    -3.14   0.002    -.0245259   -.0056669
                   14436  |  -.0075136   .0049397    -1.52   0.128    -.0171954    .0021682
                   14438  |  -.0084253   .0049812    -1.69   0.091    -.0181885    .0013378
                   14439  |          0  (omitted)
                   14540  |   .0054311   .0054776     0.99   0.321     -.005305    .0161671
                   14541  |   .0086967   .0041026     2.12   0.034     .0006557    .0167377
                   14542  |          0  (omitted)
                          |
                    _cons |   .0910085   .0050238    18.12   0.000     .0811621     .100855
-------------------------------------------------------------------------------------------

. 
. 
. 
. ** main effect & interaction models (TABLE D7)
. eststo clear 

. 
. eststo bas100: reg votinc i.randtreat100 i.ccaa i.randdate100, vce(cluster respid) 

Linear regression                               Number of obs     =    144,284
                                                F(32, 11048)      =      23.80
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0429
                                                Root MSE          =     .43086

                                     (Std. err. adjusted for 11,049 clusters in respid)
---------------------------------------------------------------------------------------
                      |               Robust
               votinc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
----------------------+----------------------------------------------------------------
         randtreat100 |
                post  |   .0108115   .0097407     1.11   0.267    -.0082819    .0299049
                      |
                 ccaa |
              Aragón  |   .0447055   .0257318     1.74   0.082    -.0057334    .0951445
            Asturias  |  -.0372634   .0258155    -1.44   0.149    -.0878664    .0133396
            Baleares  |   .0459185   .0341997     1.34   0.179    -.0211189     .112956
            Canarias  |   .0786498   .0244472     3.22   0.001     .0307288    .1265707
           Cantabria  |   .0747627   .0387345     1.93   0.054    -.0011639    .1506892
  Castilla-la Mancha  |   .0787312   .0238902     3.30   0.001     .0319022    .1255603
       Castilla-León  |   .1193916   .0201606     5.92   0.000     .0798732      .15891
            Cataluña  |  -.0970164   .0129658    -7.48   0.000    -.1224317   -.0716011
Comunidad Valenciana  |   .1335307   .0177606     7.52   0.000     .0987168    .1683447
          E5remadura  |   .1251196   .0293908     4.26   0.000     .0675084    .1827309
             Galicia  |   .0826505   .0199397     4.15   0.000     .0435652    .1217358
              Madrid  |   .0780262    .016466     4.74   0.000     .0457498    .1103026
              Murcia  |   .1373616   .0309706     4.44   0.000     .0766537    .1980695
             Navarra  |  -.0323032    .035762    -0.90   0.366     -.102403    .0377966
          País Vasco  |  -.1801341   .0136681   -13.18   0.000     -.206926   -.1533422
               Rioja  |   .0377727   .0524412     0.72   0.471    -.0650215    .1405669
                      |
          randdate100 |
               14181  |   .0061348   .0089033     0.69   0.491    -.0113172    .0235868
               14182  |   .0096091   .0088819     1.08   0.279     -.007801    .0270191
               14272  |    .004672   .0142156     0.33   0.742    -.0231931    .0325372
               14273  |   .0186206   .0155903     1.19   0.232    -.0119391    .0491804
               14274  |  -.0068717   .0166703    -0.41   0.680    -.0395485    .0258051
               14359  |  -.0149442   .0144889    -1.03   0.302     -.043345    .0134567
               14360  |  -.0091422   .0170563    -0.54   0.592    -.0425756    .0242913
               14361  |  -.0130232   .0165432    -0.79   0.431    -.0454508    .0194044
               14435  |   .0028268   .0139222     0.20   0.839    -.0244632    .0301168
               14436  |   .0062347   .0136041     0.46   0.647    -.0204317     .032901
               14438  |   .0128972    .015673     0.82   0.411    -.0178248    .0436191
               14439  |   .0142067   .0154822     0.92   0.359    -.0161412    .0445546
               14540  |   .0034519   .0144491     0.24   0.811    -.0248709    .0317746
               14541  |   .0051082   .0139541     0.37   0.714    -.0222443    .0324607
               14542  |  -.0007576   .0148101    -0.05   0.959    -.0297881    .0282729
                      |
                _cons |   .2274355   .0153752    14.79   0.000     .1972973    .2575737
---------------------------------------------------------------------------------------

. estadd local controls "No"

added macro:
           e(controls) : "No"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "No"

added macro:
                e(imb) : "No"

. estadd local n = e(N)

added macro:
                  e(n) : "144284"

. 
. eststo bascon100: reg votinc i.randtreat100 female c.age##c.age edu i.emplo i.munsz i.ccaa i.randdate100,
>  vce(cluster respid) 

Linear regression                               Number of obs     =    130,155
                                                F(46, 9965)       =      19.71
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0607
                                                Root MSE          =      .4291

                                               (Std. err. adjusted for 9,966 clusters in respid)
------------------------------------------------------------------------------------------------
                               |               Robust
                        votinc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------------------+----------------------------------------------------------------
                  randtreat100 |
                         post  |   .0176058   .0102399     1.72   0.086    -.0024665    .0376781
                        female |  -.0292391   .0099254    -2.95   0.003    -.0486949   -.0097833
                           age |   .0020282   .0015974     1.27   0.204     -.001103    .0051594
                               |
                   c.age#c.age |   1.45e-06    .000017     0.09   0.932    -.0000318    .0000347
                               |
                           edu |   .0175022   .0023906     7.32   0.000     .0128162    .0221882
                               |
                         emplo |
                   unemployed  |  -.0001624   .0151955    -0.01   0.991    -.0299487    .0296238
                      student  |   .0260195   .0193979     1.34   0.180    -.0120043    .0640433
                      retired  |   .0460359   .0185178     2.49   0.013     .0097372    .0823345
                    housework  |   .0487454   .0152152     3.20   0.001     .0189206    .0785702
                               |
                         munsz |
    2.001 a 10.000 habitantes  |  -.0691016   .0198801    -3.48   0.001    -.1080707   -.0301325
   10.001 a 50.000 habitantes  |  -.0670584   .0192011    -3.49   0.000    -.1046965   -.0294203
  50.001 a 100.000 habitantes  |  -.0571173   .0219892    -2.60   0.009    -.1002206   -.0140139
   100001 a 400000 habitantes  |  -.0396461   .0194463    -2.04   0.042    -.0777647   -.0015274
400001 a 1.000.000 habitantes  |  -.0690823   .0258417    -2.67   0.008    -.1197373   -.0184273
  Más de 1.000.000 habitantes  |  -.0588711   .0237727    -2.48   0.013    -.1054705   -.0122718
                               |
                          ccaa |
                       Aragón  |  -.0003275   .0280609    -0.01   0.991    -.0553327    .0546776
                     Asturias  |  -.0896948   .0272608    -3.29   0.001    -.1431315   -.0362581
                     Baleares  |   .0088867   .0355859     0.25   0.803    -.0608689    .0786423
                     Canarias  |   .0586546   .0269573     2.18   0.030     .0058129    .1114963
                    Cantabria  |   .0210187   .0392834     0.54   0.593    -.0559846     .098022
           Castilla-la Mancha  |   .0517137    .026831     1.93   0.054    -.0008804    .1043078
                Castilla-León  |   .0587695   .0218113     2.69   0.007      .016015    .1015239
                     Cataluña  |  -.1338912   .0154025    -8.69   0.000    -.1640833   -.1036991
         Comunidad Valenciana  |   .1056992   .0189984     5.56   0.000     .0684586    .1429399
                   E5remadura  |   .0998235   .0332487     3.00   0.003     .0346494    .1649977
                      Galicia  |   .0464054   .0214261     2.17   0.030     .0044059    .0884048
                       Madrid  |   .0318479   .0206251     1.54   0.123    -.0085815    .0722773
                       Murcia  |   .1428449   .0345821     4.13   0.000     .0750571    .2106328
                      Navarra  |  -.0902788   .0356832    -2.53   0.011     -.160225   -.0203326
                   País Vasco  |  -.2347064    .015506   -15.14   0.000    -.2651013   -.2043114
                        Rioja  |  -.0149321   .0535243    -0.28   0.780    -.1198505    .0899864
                               |
                   randdate100 |
                        14181  |   .0070753   .0094571     0.75   0.454    -.0114626    .0256131
                        14182  |   .0130434   .0093684     1.39   0.164    -.0053206    .0314074
                        14272  |    .001674   .0149739     0.11   0.911    -.0276778    .0310259
                        14273  |   .0180153   .0164272     1.10   0.273    -.0141854    .0502159
                        14274  |  -.0043994   .0174738    -0.25   0.801    -.0386515    .0298527
                        14359  |  -.0231122   .0152916    -1.51   0.131    -.0530869    .0068626
                        14360  |  -.0147294   .0178984    -0.82   0.411    -.0498139    .0203551
                        14361  |  -.0165444   .0174461    -0.95   0.343    -.0507422    .0176534
                        14435  |   .0043018   .0147029     0.29   0.770    -.0245188    .0331224
                        14436  |   .0085344   .0143355     0.60   0.552    -.0195661    .0366349
                        14438  |   .0185592   .0165023     1.12   0.261    -.0137886    .0509071
                        14439  |   .0215822     .01632     1.32   0.186    -.0104084    .0535727
                        14540  |   .0052656   .0152044     0.35   0.729     -.024538    .0350693
                        14541  |   .0053013    .014675     0.36   0.718    -.0234647    .0340672
                        14542  |    .002169    .015643     0.14   0.890    -.0284945    .0328325
                               |
                         _cons |   .1507923   .0455041     3.31   0.001     .0615951    .2399895
------------------------------------------------------------------------------------------------

. estadd local controls "Yes"

added macro:
           e(controls) : "Yes"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "No"

added macro:
                e(imb) : "No"

. estadd local n = e(N)

added macro:
                  e(n) : "130155"

. 
. eststo basint100: reg votinc i.randtreat100##i.regattack100 i.ccaa i.randdate100, vce(cluster respid) 

Linear regression                               Number of obs     =    144,284
                                                F(34, 11048)      =      22.99
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0429
                                                Root MSE          =     .43086

                                         (Std. err. adjusted for 11,049 clusters in respid)
-------------------------------------------------------------------------------------------
                          |               Robust
                   votinc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
--------------------------+----------------------------------------------------------------
             randtreat100 |
                    post  |   .0110917   .0098323     1.13   0.259    -.0081814    .0303647
           1.regattack100 |  -.0019966   .0078265    -0.26   0.799    -.0173379    .0133447
                          |
randtreat100#regattack100 |
                  post#1  |  -.0035787   .0119449    -0.30   0.764    -.0269929    .0198355
                          |
                     ccaa |
                  Aragón  |   .0446177   .0257302     1.73   0.083    -.0058181    .0950535
                Asturias  |  -.0374387   .0258156    -1.45   0.147    -.0880419    .0131644
                Baleares  |   .0458448   .0342008     1.34   0.180    -.0211948    .1128844
                Canarias  |   .0784948   .0244477     3.21   0.001      .030573    .1264166
               Cantabria  |   .0746551   .0387355     1.93   0.054    -.0012733    .1505836
      Castilla-la Mancha  |   .0786025   .0238905     3.29   0.001     .0317729    .1254322
           Castilla-León  |   .1193217   .0201601     5.92   0.000     .0798044     .158839
                Cataluña  |  -.0970012   .0129677    -7.48   0.000    -.1224203   -.0715822
    Comunidad Valenciana  |   .1334272   .0177614     7.51   0.000     .0986117    .1682427
              E5remadura  |   .1250006   .0293921     4.25   0.000     .0673869    .1826143
                 Galicia  |    .082679   .0199404     4.15   0.000     .0435922    .1217658
                  Madrid  |   .0789333    .016486     4.79   0.000     .0466178    .1112488
                  Murcia  |   .1372056   .0309702     4.43   0.000     .0764985    .1979127
                 Navarra  |  -.0322105   .0357627    -0.90   0.368    -.1023118    .0378907
              País Vasco  |  -.1779221   .0139253   -12.78   0.000    -.2052183    -.150626
                   Rioja  |   .0376514    .052439     0.72   0.473    -.0651385    .1404413
                          |
              randdate100 |
                   14181  |   .0060987   .0089015     0.69   0.493    -.0113498    .0235472
                   14182  |   .0096276   .0088822     1.08   0.278    -.0077831    .0270383
                   14272  |   .0046332   .0142146     0.33   0.744    -.0232299    .0324964
                   14273  |   .0185677   .0155876     1.19   0.234    -.0119868    .0491222
                   14274  |  -.0067729   .0166641    -0.41   0.684    -.0394376    .0258917
                   14359  |  -.0148549   .0144917    -1.03   0.305    -.0432611    .0135514
                   14360  |   -.008965   .0170534    -0.53   0.599    -.0423927    .0244628
                   14361  |  -.0129434    .016542    -0.78   0.434    -.0453687    .0194819
                   14435  |   .0030304   .0139086     0.22   0.828    -.0242329    .0302938
                   14436  |   .0062418   .0136041     0.46   0.646    -.0204246    .0329082
                   14438  |   .0130068   .0156682     0.83   0.406    -.0177056    .0437192
                   14439  |   .0142234   .0154852     0.92   0.358    -.0161303    .0445772
                   14540  |   .0033644   .0144532     0.23   0.816    -.0249665    .0316953
                   14541  |   .0052275   .0139526     0.37   0.708    -.0221221    .0325772
                   14542  |    -.00062   .0148073    -0.04   0.967    -.0296449     .028405
                          |
                    _cons |   .2273568   .0154093    14.75   0.000     .1971518    .2575618
-------------------------------------------------------------------------------------------

. estadd local controls "No"

added macro:
           e(controls) : "No"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "No"

added macro:
                e(imb) : "No"

. estadd local n = e(N)                

added macro:
                  e(n) : "144284"

. 
. eststo basinccon100: reg votinc i.randtreat100##i.regattack100 female c.age##c.age edu i.emplo i.munsz i.
> ccaa i.randdate100, vce(cluster respid) 

Linear regression                               Number of obs     =    130,155
                                                F(48, 9965)       =      19.23
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0607
                                                Root MSE          =      .4291

                                               (Std. err. adjusted for 9,966 clusters in respid)
------------------------------------------------------------------------------------------------
                               |               Robust
                        votinc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
-------------------------------+----------------------------------------------------------------
                  randtreat100 |
                         post  |   .0180804   .0103539     1.75   0.081    -.0022153    .0383761
                1.regattack100 |   .0008022   .0081773     0.10   0.922    -.0152269    .0168314
                               |
     randtreat100#regattack100 |
                       post#1  |  -.0058843   .0122881    -0.48   0.632    -.0299715    .0182029
                               |
                        female |  -.0292402   .0099254    -2.95   0.003    -.0486961   -.0097843
                           age |   .0020262   .0015975     1.27   0.205    -.0011051    .0051576
                               |
                   c.age#c.age |   1.47e-06    .000017     0.09   0.931    -.0000318    .0000347
                               |
                           edu |   .0175031   .0023906     7.32   0.000     .0128171    .0221892
                               |
                         emplo |
                   unemployed  |  -.0001806   .0151962    -0.01   0.991    -.0299682     .029607
                      student  |   .0260191   .0193977     1.34   0.180    -.0120042    .0640424
                      retired  |   .0460167    .018517     2.49   0.013     .0097197    .0823136
                    housework  |   .0487372    .015215     3.20   0.001     .0189127    .0785617
                               |
                         munsz |
    2.001 a 10.000 habitantes  |  -.0690874   .0198799    -3.48   0.001     -.108056   -.0301188
   10.001 a 50.000 habitantes  |  -.0670653   .0192012    -3.49   0.000    -.1047036    -.029427
  50.001 a 100.000 habitantes  |  -.0572028   .0219932    -2.60   0.009     -.100314   -.0140917
   100001 a 400000 habitantes  |   -.039623   .0194457    -2.04   0.042    -.0777404   -.0015055
400001 a 1.000.000 habitantes  |  -.0690897    .025842    -2.67   0.008    -.1197453   -.0184342
  Más de 1.000.000 habitantes  |  -.0588552   .0237723    -2.48   0.013    -.1054538   -.0122567
                               |
                          ccaa |
                       Aragón  |  -.0003649   .0280596    -0.01   0.990    -.0553673    .0546375
                     Asturias  |  -.0898176   .0272611    -3.29   0.001    -.1432548   -.0363804
                     Baleares  |   .0089189   .0355886     0.25   0.802     -.060842    .0786798
                     Canarias  |    .058553   .0269581     2.17   0.030     .0057097    .1113963
                    Cantabria  |   .0209919   .0392855     0.53   0.593    -.0560157    .0979995
           Castilla-la Mancha  |   .0516757    .026831     1.93   0.054    -.0009184    .1042698
                Castilla-León  |    .058768   .0218109     2.69   0.007     .0160143    .1015217
                     Cataluña  |  -.1338455   .0154044    -8.69   0.000    -.1640412   -.1036498
         Comunidad Valenciana  |   .1056951   .0189997     5.56   0.000     .0684519    .1429384
                   E5remadura  |   .0997946   .0332491     3.00   0.003     .0346197    .1649695
                      Galicia  |   .0464539   .0214273     2.17   0.030     .0044521    .0884558
                       Madrid  |   .0324036   .0206508     1.57   0.117    -.0080762    .0728833
                       Murcia  |   .1427503   .0345819     4.13   0.000     .0749628    .2105377
                      Navarra  |  -.0902561   .0356828    -2.53   0.011    -.1602015   -.0203106
                   País Vasco  |  -.2330072   .0156718   -14.87   0.000     -.263727   -.2022873
                        Rioja  |  -.0150565   .0535222    -0.28   0.778    -.1199709    .0898579
                               |
                   randdate100 |
                        14181  |   .0070765   .0094567     0.75   0.454    -.0114605    .0256135
                        14182  |   .0130722   .0093696     1.40   0.163    -.0052941    .0314386
                        14272  |    .001644    .014973     0.11   0.913    -.0277061     .030994
                        14273  |   .0179549   .0164241     1.09   0.274    -.0142396    .0501494
                        14274  |  -.0043877   .0174655    -0.25   0.802    -.0386235    .0298482
                        14359  |   -.023008    .015295    -1.50   0.133    -.0529893    .0069733
                        14360  |  -.0145509   .0178956    -0.81   0.416    -.0496299    .0205282
                        14361  |  -.0165042   .0174439    -0.95   0.344    -.0506979    .0176894
                        14435  |   .0044743   .0146872     0.30   0.761    -.0243156    .0332643
                        14436  |   .0085887   .0143354     0.60   0.549    -.0195116    .0366891
                        14438  |   .0186039   .0164964     1.13   0.259    -.0137324    .0509403
                        14439  |   .0216408   .0163241     1.33   0.185    -.0103577    .0536394
                        14540  |   .0052295   .0152098     0.34   0.731    -.0245847    .0350437
                        14541  |   .0054301    .014675     0.37   0.711    -.0233359    .0341961
                        14542  |   .0022756   .0156407     0.15   0.884    -.0283834    .0329346
                               |
                         _cons |   .1505679   .0454969     3.31   0.001     .0613848     .239751
------------------------------------------------------------------------------------------------

. estadd local controls "Yes"

added macro:
           e(controls) : "Yes"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "No"

added macro:
                e(imb) : "No"

. estadd local n = e(N)

added macro:
                  e(n) : "130155"

.                    
. eststo basincconimb100: reg votinc i.randtreat100##i.regattack100 female c.age##c.age edu i.emplo##i.rega
> ttack100 i.munsz##i.regattack100 i.ccaa i.randdate100, vce(cluster respid)  

Linear regression                               Number of obs     =    130,155
                                                F(58, 9965)       =      17.32
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0610
                                                Root MSE          =     .42905

                                                 (Std. err. adjusted for 9,966 clusters in respid)
--------------------------------------------------------------------------------------------------
                                 |               Robust
                          votinc | Coefficient  std. err.      t    P>|t|     [95% conf. interval]
---------------------------------+----------------------------------------------------------------
                    randtreat100 |
                           post  |    .018112    .010352     1.75   0.080    -.0021801    .0384041
                  1.regattack100 |  -.0445128   .0259399    -1.72   0.086    -.0953603    .0063346
                                 |
       randtreat100#regattack100 |
                         post#1  |  -.0031687   .0120132    -0.26   0.792     -.026717    .0203795
                                 |
                          female |  -.0291278    .009923    -2.94   0.003    -.0485789   -.0096768
                             age |    .002038   .0015974     1.28   0.202    -.0010931    .0051692
                                 |
                     c.age#c.age |   1.27e-06    .000017     0.07   0.940     -.000032    .0000345
                                 |
                             edu |   .0174889   .0023902     7.32   0.000     .0128035    .0221742
                                 |
                           emplo |
                     unemployed  |   .0009888   .0156541     0.06   0.950    -.0296964    .0316741
                        student  |   .0221264   .0197721     1.12   0.263    -.0166309    .0608837
                        retired  |   .0476658   .0188117     2.53   0.011     .0107912    .0845405
                      housework  |    .046314   .0154625     3.00   0.003     .0160043    .0766237
                                 |
              emplo#regattack100 |
                   unemployed#1  |  -.0179322   .0235261    -0.76   0.446    -.0640482    .0281837
                      student#1  |   .0434746   .0268965     1.62   0.106    -.0092478    .0961971
                      retired#1  |  -.0161042   .0198678    -0.81   0.418    -.0550491    .0228406
                    housework#1  |   .0320653   .0203272     1.58   0.115    -.0077802    .0719107
                                 |
                           munsz |
      2.001 a 10.000 habitantes  |  -.0705911   .0203917    -3.46   0.001    -.1105629   -.0306194
     10.001 a 50.000 habitantes  |  -.0702563   .0197212    -3.56   0.000    -.1089137   -.0315988
    50.001 a 100.000 habitantes  |  -.0621846   .0225385    -2.76   0.006    -.1063646   -.0180045
     100001 a 400000 habitantes  |  -.0400475   .0200563    -2.00   0.046    -.0793619   -.0007331
  400001 a 1.000.000 habitantes  |  -.0706318   .0261352    -2.70   0.007    -.1218621   -.0194015
    Más de 1.000.000 habitantes  |  -.0611318   .0237949    -2.57   0.010    -.1077747   -.0144889
                                 |
              munsz#regattack100 |
    2.001 a 10.000 habitantes#1  |   .0266201   .0281524     0.95   0.344    -.0285642    .0818045
   10.001 a 50.000 habitantes#1  |    .055697   .0270925     2.06   0.040     .0025902    .1088039
  50.001 a 100.000 habitantes#1  |   .0788293   .0353737     2.23   0.026     .0094898    .1481689
   100001 a 400000 habitantes#1  |    .024358    .026706     0.91   0.362    -.0279911     .076707
400001 a 1.000.000 habitantes#1  |   .0160841   .0404079     0.40   0.691    -.0631235    .0952918
  Más de 1.000.000 habitantes#1  |   .0439789   .0260953     1.69   0.092    -.0071732    .0951309
                                 |
                            ccaa |
                         Aragón  |  -.0009506   .0280646    -0.03   0.973    -.0559628    .0540616
                       Asturias  |  -.0903014   .0272814    -3.31   0.001    -.1437785   -.0368243
                       Baleares  |   .0082368   .0355983     0.23   0.817     -.061543    .0780166
                       Canarias  |   .0581339   .0269584     2.16   0.031       .00529    .1109778
                      Cantabria  |   .0200611   .0392938     0.51   0.610    -.0569626    .0970849
             Castilla-la Mancha  |    .051797   .0268392     1.93   0.054    -.0008131    .1044072
                  Castilla-León  |   .0582108    .021825     2.67   0.008     .0154293    .1009923
                       Cataluña  |  -.1341046   .0153897    -8.71   0.000    -.1642716   -.1039376
           Comunidad Valenciana  |   .1056614   .0190082     5.56   0.000     .0684015    .1429214
                     E5remadura  |   .0994252   .0332746     2.99   0.003     .0342002    .1646502
                        Galicia  |   .0462365    .021426     2.16   0.031     .0042372    .0882358
                         Madrid  |   .0314291   .0206612     1.52   0.128     -.009071    .0719292
                         Murcia  |   .1426498   .0345877     4.12   0.000     .0748509    .2104487
                        Navarra  |  -.0902197   .0356613    -2.53   0.011     -.160123   -.0203164
                     País Vasco  |  -.2324941    .015661   -14.85   0.000    -.2631929   -.2017953
                          Rioja  |  -.0163504   .0535323    -0.31   0.760    -.1212846    .0885838
                                 |
                     randdate100 |
                          14181  |   .0075523   .0094499     0.80   0.424    -.0109714    .0260761
                          14182  |   .0131945   .0093732     1.41   0.159     -.005179    .0315679
                          14272  |   .0019707   .0149711     0.13   0.895    -.0273757    .0313171
                          14273  |   .0179052    .016415     1.09   0.275    -.0142716     .050082
                          14274  |  -.0039793   .0174512    -0.23   0.820    -.0381872    .0302286
                          14359  |  -.0225494   .0152879    -1.47   0.140    -.0525167    .0074179
                          14360  |  -.0142138   .0178871    -0.79   0.427    -.0492761    .0208485
                          14361  |  -.0162929   .0174198    -0.94   0.350    -.0504392    .0178533
                          14435  |    .004379   .0146937     0.30   0.766    -.0244237    .0331817
                          14436  |   .0086421   .0143272     0.60   0.546    -.0194422    .0367263
                          14438  |   .0187941   .0164741     1.14   0.254    -.0134985    .0510867
                          14439  |   .0218016   .0163123     1.34   0.181    -.0101738     .053777
                          14540  |   .0054391   .0152024     0.36   0.721    -.0243607     .035239
                          14541  |   .0054199   .0146664     0.37   0.712    -.0233292     .034169
                          14542  |   .0027016    .015617     0.17   0.863    -.0279109    .0333142
                                 |
                           _cons |   .1528411   .0456922     3.35   0.001     .0632752     .242407
--------------------------------------------------------------------------------------------------

. estadd local controls "Yes"

added macro:
           e(controls) : "Yes"

. estadd local attack_fe "Yes"

added macro:
          e(attack_fe) : "Yes"

. estadd local region_fe "Yes"

added macro:
          e(region_fe) : "Yes"

. estadd local imb "Yes"

added macro:
                e(imb) : "Yes"

. estadd local n = e(N)

added macro:
                  e(n) : "130155"

. 
. 
. ** TABLE D7
. esttab bas100 bascon100 basint100 basinccon100 basincconimb100 ///
> , replace noomitted label nonotes noobs nodepvar nomtitles ///
> keep(1.randtreat100 1.regattack100 1.randtreat100#1.regattack100) ///
>  coeflabels(1.randtreat100 "Post" 1.regattack100 "Target region" 1.randtreat100#1.regattack100 "Post X Ta
> rget") ///
>  b(%9.2f) se(%9.2f) ///
>  scalars("controls Controls" "attack_fe False Attack FE" "region_fe Region FE" "imb Imbalance inter." "n 
> N. of observations") ///
>  interaction(" $\times$ ") ///
>  starlevels(+ 0.1 * 0.05 ** 0.01 *** 0.001) ///
>  addnotes("Standard errors in parentheses" "+ p<.10, * p<.05, ** p<.01, *** p<.001.")

----------------------------------------------------------------------------------------------------
                              (1)             (2)             (3)             (4)             (5)   
----------------------------------------------------------------------------------------------------
Post                         0.01            0.02+           0.01            0.02+           0.02+  
                           (0.01)          (0.01)          (0.01)          (0.01)          (0.01)   

Target region                                               -0.00            0.00           -0.04+  
                                                           (0.01)          (0.01)          (0.03)   

Post X Target                                               -0.00           -0.01           -0.00   
                                                           (0.01)          (0.01)          (0.01)   
----------------------------------------------------------------------------------------------------
Controls                       No             Yes              No             Yes             Yes   
False Attack FE               Yes             Yes             Yes             Yes             Yes   
Region FE                     Yes             Yes             Yes             Yes             Yes   
Imbalance inter.               No              No              No              No             Yes   
N. of observations         144284          130155          144284          130155          130155   
----------------------------------------------------------------------------------------------------
Standard errors in parentheses
+ p<.10, * p<.05, ** p<.01, *** p<.001.

. 
. eststo clear 

. 
. log close
      name:  <unnamed>
       log:  C:\Users\1313537\Dropbox\Ramon y Cajal UAB\2024-2025\Multiple UESDs paper\PSRM R&R\placebo rep
> lication material\Placebo Preplication (Section D.6).log
  log type:  text
 closed on:  10 Feb 2025, 17:11:42
-----------------------------------------------------------------------------------------------------------
